what is a introduction grammar

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How to Write an Essay Introduction (with Examples)   

The introduction of an essay plays a critical role in engaging the reader and providing contextual information about the topic. It sets the stage for the rest of the essay, establishes the tone and style, and motivates the reader to continue reading. 

Table of Contents

What is an essay introduction , what to include in an essay introduction, how to create an essay structure , step-by-step process for writing an essay introduction , how to write an introduction paragraph , how to write a hook for your essay , how to include background information , how to write a thesis statement .

• Argumentative Essay Introduction Example: 
• Expository Essay Introduction Example 

Literary Analysis Essay Introduction Example

Check and revise – checklist for essay introduction , key takeaways , frequently asked questions .

An introduction is the opening section of an essay, paper, or other written work. It introduces the topic and provides background information, context, and an overview of what the reader can expect from the rest of the work. 1 The key is to be concise and to the point, providing enough information to engage the reader without delving into excessive detail. 

The essay introduction is crucial as it sets the tone for the entire piece and provides the reader with a roadmap of what to expect. Here are key elements to include in your essay introduction: 

• Hook : Start with an attention-grabbing statement or question to engage the reader. This could be a surprising fact, a relevant quote, or a compelling anecdote. 
• Background information : Provide context and background information to help the reader understand the topic. This can include historical information, definitions of key terms, or an overview of the current state of affairs related to your topic. 
• Thesis statement : Clearly state your main argument or position on the topic. Your thesis should be concise and specific, providing a clear direction for your essay. 

Before we get into how to write an essay introduction, we need to know how it is structured. The structure of an essay is crucial for organizing your thoughts and presenting them clearly and logically. It is divided as follows: 2  

• Introduction:  The introduction should grab the reader’s attention with a hook, provide context, and include a thesis statement that presents the main argument or purpose of the essay.  
• Body:  The body should consist of focused paragraphs that support your thesis statement using evidence and analysis. Each paragraph should concentrate on a single central idea or argument and provide evidence, examples, or analysis to back it up.  
• Conclusion:  The conclusion should summarize the main points and restate the thesis differently. End with a final statement that leaves a lasting impression on the reader. Avoid new information or arguments. 

Here’s a step-by-step guide on how to write an essay introduction: 

• Start with a Hook : Begin your introduction paragraph with an attention-grabbing statement, question, quote, or anecdote related to your topic. The hook should pique the reader’s interest and encourage them to continue reading. 
• Provide Background Information : This helps the reader understand the relevance and importance of the topic. 
• State Your Thesis Statement : The last sentence is the main argument or point of your essay. It should be clear, concise, and directly address the topic of your essay. 
• Preview the Main Points : This gives the reader an idea of what to expect and how you will support your thesis. 
• Keep it Concise and Clear : Avoid going into too much detail or including information not directly relevant to your topic. 
• Revise : Revise your introduction after you’ve written the rest of your essay to ensure it aligns with your final argument. 

Here’s an example of an essay introduction paragraph about the importance of education: 

Education is often viewed as a fundamental human right and a key social and economic development driver. As Nelson Mandela once famously said, “Education is the most powerful weapon which you can use to change the world.” It is the key to unlocking a wide range of opportunities and benefits for individuals, societies, and nations. In today’s constantly evolving world, education has become even more critical. It has expanded beyond traditional classroom learning to include digital and remote learning, making education more accessible and convenient. This essay will delve into the importance of education in empowering individuals to achieve their dreams, improving societies by promoting social justice and equality, and driving economic growth by developing a skilled workforce and promoting innovation. 

This introduction paragraph example includes a hook (the quote by Nelson Mandela), provides some background information on education, and states the thesis statement (the importance of education). 

This is one of the key steps in how to write an essay introduction. Crafting a compelling hook is vital because it sets the tone for your entire essay and determines whether your readers will stay interested. A good hook draws the reader in and sets the stage for the rest of your essay.  

• Avoid Dry Fact : Instead of simply stating a bland fact, try to make it engaging and relevant to your topic. For example, if you’re writing about the benefits of exercise, you could start with a startling statistic like, “Did you know that regular exercise can increase your lifespan by up to seven years?” 
• Avoid Using a Dictionary Definition : While definitions can be informative, they’re not always the most captivating way to start an essay. Instead, try to use a quote, anecdote, or provocative question to pique the reader’s interest. For instance, if you’re writing about freedom, you could begin with a quote from a famous freedom fighter or philosopher. 
• Do Not Just State a Fact That the Reader Already Knows : This ties back to the first point—your hook should surprise or intrigue the reader. For Here’s an introduction paragraph example, if you’re writing about climate change, you could start with a thought-provoking statement like, “Despite overwhelming evidence, many people still refuse to believe in the reality of climate change.” 

Including background information in the introduction section of your essay is important to provide context and establish the relevance of your topic. When writing the background information, you can follow these steps: 

• Start with a General Statement:  Begin with a general statement about the topic and gradually narrow it down to your specific focus. For example, when discussing the impact of social media, you can begin by making a broad statement about social media and its widespread use in today’s society, as follows: “Social media has become an integral part of modern life, with billions of users worldwide.” 
• Define Key Terms : Define any key terms or concepts that may be unfamiliar to your readers but are essential for understanding your argument. 
• Provide Relevant Statistics:  Use statistics or facts to highlight the significance of the issue you’re discussing. For instance, “According to a report by Statista, the number of social media users is expected to reach 4.41 billion by 2025.” 
• Discuss the Evolution:  Mention previous research or studies that have been conducted on the topic, especially those that are relevant to your argument. Mention key milestones or developments that have shaped its current impact. You can also outline some of the major effects of social media. For example, you can briefly describe how social media has evolved, including positives such as increased connectivity and issues like cyberbullying and privacy concerns. 
• Transition to Your Thesis:  Use the background information to lead into your thesis statement, which should clearly state the main argument or purpose of your essay. For example, “Given its pervasive influence, it is crucial to examine the impact of social media on mental health.” 

A thesis statement is a concise summary of the main point or claim of an essay, research paper, or other type of academic writing. It appears near the end of the introduction. Here’s how to write a thesis statement: 

• Identify the topic:  Start by identifying the topic of your essay. For example, if your essay is about the importance of exercise for overall health, your topic is “exercise.” 
• State your position:  Next, state your position or claim about the topic. This is the main argument or point you want to make. For example, if you believe that regular exercise is crucial for maintaining good health, your position could be: “Regular exercise is essential for maintaining good health.” 
• Support your position:  Provide a brief overview of the reasons or evidence that support your position. These will be the main points of your essay. For example, if you’re writing an essay about the importance of exercise, you could mention the physical health benefits, mental health benefits, and the role of exercise in disease prevention. 
• Make it specific:  Ensure your thesis statement clearly states what you will discuss in your essay. For example, instead of saying, “Exercise is good for you,” you could say, “Regular exercise, including cardiovascular and strength training, can improve overall health and reduce the risk of chronic diseases.” 

Examples of essay introduction 

Here are examples of essay introductions for different types of essays: 

Argumentative Essay Introduction Example:  

Topic: Should the voting age be lowered to 16? 

“The question of whether the voting age should be lowered to 16 has sparked nationwide debate. While some argue that 16-year-olds lack the requisite maturity and knowledge to make informed decisions, others argue that doing so would imbue young people with agency and give them a voice in shaping their future.” 

Expository Essay Introduction Example  

Topic: The benefits of regular exercise 

“In today’s fast-paced world, the importance of regular exercise cannot be overstated. From improving physical health to boosting mental well-being, the benefits of exercise are numerous and far-reaching. This essay will examine the various advantages of regular exercise and provide tips on incorporating it into your daily routine.” 

Text: “To Kill a Mockingbird” by Harper Lee 

“Harper Lee’s novel, ‘To Kill a Mockingbird,’ is a timeless classic that explores themes of racism, injustice, and morality in the American South. Through the eyes of young Scout Finch, the reader is taken on a journey that challenges societal norms and forces characters to confront their prejudices. This essay will analyze the novel’s use of symbolism, character development, and narrative structure to uncover its deeper meaning and relevance to contemporary society.” 

• Engaging and Relevant First Sentence : The opening sentence captures the reader’s attention and relates directly to the topic. 
• Background Information : Enough background information is introduced to provide context for the thesis statement. 
• Definition of Important Terms : Key terms or concepts that might be unfamiliar to the audience or are central to the argument are defined. 
• Clear Thesis Statement : The thesis statement presents the main point or argument of the essay. 
• Relevance to Main Body : Everything in the introduction directly relates to and sets up the discussion in the main body of the essay. 

Writing a strong introduction is crucial for setting the tone and context of your essay. Here are the key takeaways for how to write essay introduction: 3  

• Hook the Reader : Start with an engaging hook to grab the reader’s attention. This could be a compelling question, a surprising fact, a relevant quote, or an anecdote. 
• Provide Background : Give a brief overview of the topic, setting the context and stage for the discussion. 
• Thesis Statement : State your thesis, which is the main argument or point of your essay. It should be concise, clear, and specific. 
• Preview the Structure : Outline the main points or arguments to help the reader understand the organization of your essay. 
• Keep it Concise : Avoid including unnecessary details or information not directly related to your thesis. 
• Revise and Edit : Revise your introduction to ensure clarity, coherence, and relevance. Check for grammar and spelling errors. 
• Seek Feedback : Get feedback from peers or instructors to improve your introduction further. 

The purpose of an essay introduction is to give an overview of the topic, context, and main ideas of the essay. It is meant to engage the reader, establish the tone for the rest of the essay, and introduce the thesis statement or central argument.  

An essay introduction typically ranges from 5-10% of the total word count. For example, in a 1,000-word essay, the introduction would be roughly 50-100 words. However, the length can vary depending on the complexity of the topic and the overall length of the essay.

An essay introduction is critical in engaging the reader and providing contextual information about the topic. To ensure its effectiveness, consider incorporating these key elements: a compelling hook, background information, a clear thesis statement, an outline of the essay’s scope, a smooth transition to the body, and optional signposting sentences.  

The process of writing an essay introduction is not necessarily straightforward, but there are several strategies that can be employed to achieve this end. When experiencing difficulty initiating the process, consider the following techniques: begin with an anecdote, a quotation, an image, a question, or a startling fact to pique the reader’s interest. It may also be helpful to consider the five W’s of journalism: who, what, when, where, why, and how.   For instance, an anecdotal opening could be structured as follows: “As I ascended the stage, momentarily blinded by the intense lights, I could sense the weight of a hundred eyes upon me, anticipating my next move. The topic of discussion was climate change, a subject I was passionate about, and it was my first public speaking event. Little did I know , that pivotal moment would not only alter my perspective but also chart my life’s course.” 

Crafting a compelling thesis statement for your introduction paragraph is crucial to grab your reader’s attention. To achieve this, avoid using overused phrases such as “In this paper, I will write about” or “I will focus on” as they lack originality. Instead, strive to engage your reader by substantiating your stance or proposition with a “so what” clause. While writing your thesis statement, aim to be precise, succinct, and clear in conveying your main argument.  

To create an effective essay introduction, ensure it is clear, engaging, relevant, and contains a concise thesis statement. It should transition smoothly into the essay and be long enough to cover necessary points but not become overwhelming. Seek feedback from peers or instructors to assess its effectiveness. 

References  

• Cui, L. (2022). Unit 6 Essay Introduction.  Building Academic Writing Skills . 
• West, H., Malcolm, G., Keywood, S., & Hill, J. (2019). Writing a successful essay.  Journal of Geography in Higher Education ,  43 (4), 609-617. 
• Beavers, M. E., Thoune, D. L., & McBeth, M. (2023). Bibliographic Essay: Reading, Researching, Teaching, and Writing with Hooks: A Queer Literacy Sponsorship. College English, 85(3), 230-242. 

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PRESCRIPTIVE VS. DESCRIPTIVE

Some people feel that grammar is prescriptive ; that is, it prescribes a set of rules telling you what is correct and incorrect at all times. However, because language usage changes over time, some people feel that grammar merely describes how people actually use a language, which implies there are gray areas in which more than one choice may be "correct."

For instance, you may have heard that in correct grammar, you should not split infinitives (the basic form of a verb such as to be ). A famous example is To boldly go where no man has gone before . However, this "rule" only goes back to the 19th century, when some linguists were trying to make the rules of English mimic the rules of Latin. Split infinitives in English were used for centuries before that.

This does not mean that any grammatical choice is acceptable for, say, college papers or other kinds of formal writing. The best thing to do if you want to break a grammar rule in college is to find a book that says your choice is an acceptable alternative (see the tab "Grammar Resources").

Grammar is the whole system and structure of a language or of languages in general. It includes parts of speech (nouns, verbs, etc.), syntax (how words fit together to make sentences), and morphology (the forms of words); many people use the term "grammar" loosely so that it also covers punctuation, spelling, and word choice (as in, "Will you check my paper's grammar?").

Grammar may seem very complicated, but m ost of it is already in your head. You may not be able to tell someone what a subordinate clause or a conjunctive adverb is, but you have internalized grammar since you first learned to talk. You use it every time you speak or write, and you mostly use it correctly.

If you really want, you can learn all the grammar rules from scratch, but most people find it more effective to concentrate on common errors and on resources you can consult when you have a question. This learning guide will concentrate on those things.

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A brief introduction to grammar

Unit 1: parts of speech: the noun, unit 2: parts of speech: the verb, unit 3: parts of speech: the pronoun, unit 4: parts of speech: the modifier, unit 5: parts of speech: the preposition and the conjunction, unit 6: punctuation: the comma and the apostrophe, unit 7: punctuation: the colon, semicolon, and more, unit 8: syntax: sentences and clauses, unit 9: syntax: conventions of standard english, unit 10: usage and style.

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Conceptions of grammar

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grammar , rules of a language governing the sounds, words, sentences, and other elements, as well as their combination and interpretation. The word grammar also denotes the study of these abstract features or a book presenting these rules. In a restricted sense, the term refers only to the study of sentence and word structure (syntax and morphology), excluding vocabulary and pronunciation.

A brief treatment of grammar follows. For full treatment, see linguistics .

A common contemporary definition of grammar is the underlying structure of a language that any native speaker of that language knows intuitively. The systematic description of the features of a language is also a grammar. These features are the phonology (sound), morphology (system of word formation), syntax (patterns of word arrangement), and semantics (meaning). Depending on the grammarian’s approach, a grammar can be prescriptive ( i.e., provide rules for correct usage), descriptive ( i.e., describe how a language is actually used), or generative ( i.e., provide instructions for the production of an infinite number of sentences in a language). The traditional focus of inquiry has been on morphology and syntax , and for some contemporary linguists (and many traditional grammarians) this is the only proper domain of the subject.

In Europe the Greeks were the first to write grammars . To them, grammar was a tool that could be used in the study of Greek literature; hence their focus on the literary language. The Alexandrians of the 1st century bc further developed Greek grammar in order to preserve the purity of the language. Dionysus Thrax of Alexandria later wrote an influential treatise called The Art of Grammar, in which he analyzed literary texts in terms of letters, syllables, and eight parts of speech .

The Romans adopted the grammatical system of the Greeks and applied it to Latin . Except for Varro , of the 1st century bc , who believed that grammarians should discover structures, not dictate them, most Latin grammarians did not attempt to alter the Greek system and also sought to protect their language from decay. Whereas the model for the Greeks and Alexandrians was the language of Homer, the works of Cicero and Virgil set the Latin standard. The works of Donatus (4th century ad ) and Priscian (6th century ad ), the most important Latin grammarians, were widely used to teach Latin grammar during the European Middle Ages . In medieval Europe, education was conducted in Latin, and Latin grammar became the foundation of the liberal arts curriculum. Many grammars were composed for students during this time. Aelfric , the abbot of Eynsham (11th century), who wrote the first Latin grammar in Anglo-Saxon, proposed that this work serve as an introduction to English grammar as well. Thus began the tradition of analyzing English grammar according to a Latin model.

The modistae , grammarians of the mid-13th to mid-14th century who viewed language as a reflection of reality, looked to philosophy for explanations of grammatical rules. The modistae sought one “universal” grammar that would serve as a means of understanding the nature of being. In 17th-century France a group of grammarians from Port-Royal were also interested in the idea of universal grammar . They claimed that common elements of thought could be discerned in grammatical categories of all languages. Unlike their Greek and Latin counterparts, the Port-Royal grammarians did not study literary language but claimed instead that usage should be dictated by the actual speech of living languages. Noting their emphasis on linguistic universals, the contemporary linguist Noam Chomsky called the Port-Royal group the first transformational grammarians.

By 1700 grammars of 61 vernacular languages had been printed. These were written primarily for purposes of reforming, purifying, or standardizing language and were put to pedagogical use. Rules of grammar usually accounted for formal, written, literary language only and did not apply to all the varieties of actual, spoken language. This prescriptive approach long dominated the schools, where the study of grammar came to be associated with “parsing” and sentence diagramming. Opposition to teaching solely in terms of prescriptive and proscriptive ( i.e. , what must not be done) rules grew during the middle decades of the 20th century.

The simplification of grammar for classroom use contrasted sharply with the complex studies that scholars of linguistics were conducting about languages. During the 19th and early 20th centuries the historical point of view flourished. Scholars who realized that every living language was in a constant state of flux studied all types of written records of modern European languages to determine the courses of their evolution. They did not limit their inquiry to literary languages but included dialects and contemporary spoken languages as well. Historical grammarians did not follow earlier prescriptive approaches but were interested, instead, in discovering where the language under study came from.

As a result of the work of historical grammarians, scholars came to see that the study of language can be either diachronic (its development through time) or synchronic (its state at a particular time). The Swiss linguist Ferdinand de Saussure and other descriptive linguists began studying the spoken language. They collected a large sample of sentences produced by native speakers of a language and classified their material starting with phonology and working their way to syntax.

Generative, or transformational , grammarians of the second half of the 20th century, such as Noam Chomsky , studied the knowledge that native speakers possess which enables them to produce and understand an infinite number of sentences. Whereas descriptivists like Saussure examined samples of individual speech to arrive at a description of a language, transformationalists first studied the underlying structure of a language. They attempted to describe the “rules” that define a native speaker’s “competence” (unconscious knowledge of the language) and account for all instances of the speaker’s “performance” (strategies the individual uses in actual sentence production). See generative grammar ; transformational grammar .

The study of grammatical theory has been of interest to philosophers, anthropologists, psychologists, and literary critics over the centuries. Today, grammar exists as a field within linguistics but still retains a relationship with these other disciplines . For many people, grammar still refers to the body of rules one must know in order to speak or write “correctly.” However, from the last quarter of the 20th century a more sophisticated awareness of grammatical issues has taken root, especially in schools. In some countries, such as Australia and the United Kingdom, new English curricula have been devised in which grammar is a focus of investigation, avoiding the prescriptivism of former times and using techniques that promote a lively and thoughtful spirit of inquiry.

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Difference between "introduction to" and "introduction of"

What exactly is the difference between "introduction to" and "introduction of"?

For example: should it be "Introduction to the problem" or "Introduction of the problem"?

• differences

4 Answers 4

There are two different meanings here:

(1) the action of introducing something issues arising from the introduction of new technology

(2) a thing preliminary to something else, especially an explanatory section at the beginning of a book, report, or speech a good general introduction to the subject is A Social History of England

From oxforddictionaries.com .

I suspect you want meaning (2):

The first paragraph provides an introduction to the problem.

It's an introduction of a problem to the people , therefore:

Let me introduce this problem to our employees. An introduction of this problem was made to our employees.

But, you can also say

I've been introduced to the problem. Our employees were introduced to the problem.

It's a matter of meaning and usage.

Both of "introduction of" and "introduction to" are grammatical and have the same meaning in the following case:

Do you mind giving us an introduction of the problem? Do you mind giving us an introduction to the problem?

But, they will have different meanings in the case below:

Your introduction to the problem will last 5 minutes. ("You" are going to be introduced) Your introduction of the problem will last 5 minutes. (The meaning here is ambiguous: 1) "You" are going to be introduced or 2) "You" are the one who introduced the problem to others)

• I have to disagree: I believe your introduction of the problem doesn't mean that you are going to be introduced to the problem, it only means the latter: that you are going to be introducing the problem to others. But I will not down-vote your answer unless someone else agrees with me by up-voting this comment. –  Frantisek Commented May 22, 2011 at 19:41

It's a matter of usage and meaning, some examples:

"Our students are learning English faster since the introduction of new classroom methods."

• Here, "Introduction of" has more to do with ideas, techniques and articles.

"With the introduction of penicillin, pneumonia was no longer as life-threatening as before."

• Here, "Introduction of" refers to bringing something into a place or situation.

"Can you give me an introduction to the president of the company?"

• "Introduction to" is more commonly used in referring to presenting someone to another person.

"Since my introduction to the use of the DVD player, I watch more movies than before."

• "introduction to" has to do with a meeting, either between people, or between a person or person, and an idea, situation, thing, etc.

So, for your case, "introduction of the problem" should be correct, according to first one.

• 4 It would be nice if you could leave a comment on why down-vote! –  user8568 Commented May 22, 2011 at 20:29

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• Introduction to Grammar

Why is it helpful to critique patterns of academic grammar and punctuation usage, including in your own work?

There are several different types of English. While there are some obvious examples of different varieties (e.g., American and British English), there are other differing types, such as formal vs. informal English or verbal vs. written English. There are also different varieties of English that are unique to cultural, societal, or professional groups.

While all of these types of English are equally dynamic and complex, each variety is appropriate in different situations. When you’re talking to your friends, you should use slang and cultural references—if you speak in formal language, you can easily come off as stiff. If you’re sending a quick casual message—via social media or texting—don’t worry too much about capitalization or strict punctuation. Feel free to have five exclamation points standing alone, if that gets your point across.

Grammar is a set of rules and conventions that dictate how Standard American English works. These rules are simply tools that speakers of a language can use. When you learn how to use the language, you can craft your message to communicate exactly what you want to convey.

Learning Outcomes

• Critique the use of nouns and pronouns.
• Critique the use of verbs.
• Critique the use other parts of speech, including adjectives, adverbs, conjunctions, prepositions, and articles.
• Critique the use of common punctuation marks.
• Critique sentence structure and variety of sentences.
• Critique the use of both active and passive voices.
• Why It Matters: Grammar. Provided by : Lumen Learning. License : CC BY: Attribution
• Toolkit. Authored by : Brian Ejar. Located at : https://thenounproject.com/term/toolkit/154266/ . License : CC BY: Attribution
• Table of Contents

Instructor Resources (available upon sign-in)

• Overview of Instructor Resources
• Quiz Survey

Reading: Types of Reading Material

• Introduction to Reading
• Outcome: Types of Reading Material
• Characteristics of Texts, Part 1
• Characteristics of Texts, Part 2
• Characteristics of Texts, Part 3
• Characteristics of Texts, Conclusion
• Self Check: Types of Writing

Reading: Reading Strategies

• Outcome: Reading Strategies
• The Rhetorical Situation
• Academic Reading Strategies
• Self Check: Reading Strategies

Reading: Specialized Reading Strategies

• Outcome: Specialized Reading Strategies
• Online Reading Comprehension
• How to Read Effectively in Math
• How to Read Effectively in the Social Sciences
• How to Read Effectively in the Sciences
• 5 Step Approach for Reading Charts and Graphs
• Self Check: Specialized Reading Strategies

Reading: Vocabulary

• Outcome: Vocabulary
• Strategies to Improve Your Vocabulary
• Using Context Clues
• The Relationship Between Reading and Vocabulary
• Self Check: Vocabulary

Reading: Thesis

• Outcome: Thesis
• Locating and Evaluating Thesis Statements
• The Organizational Statement
• Self Check: Thesis

Reading: Supporting Claims

• Outcome: Supporting Claims
• Types of Support
• Supporting Claims
• Self Check: Supporting Claims

Reading: Logic and Structure

• Outcome: Logic and Structure
• Rhetorical Modes
• Inductive and Deductive Reasoning
• Diagramming and Evaluating Arguments
• Logical Fallacies
• Evaluating Appeals to Ethos, Logos, and Pathos
• Self Check: Logic and Structure

Reading: Summary Skills

• Outcome: Summary Skills
• How to Annotate
• Paraphrasing
• Quote Bombs
• Summary Writing
• Self Check: Summary Skills
• Conclusion to Reading

Writing Process: Topic Selection

• Introduction to Writing Process
• Outcome: Topic Selection
• Starting a Paper
• Choosing and Developing Topics
• Back to the Future of Topics
• Developing Your Topic
• Self Check: Topic Selection

Writing Process: Prewriting

• Outcome: Prewriting
• Prewriting Strategies for Diverse Learners
• Rhetorical Context
• Working Thesis Statements
• Self Check: Prewriting

Writing Process: Finding Evidence

• Outcome: Finding Evidence
• Using Personal Examples
• Performing Background Research
• Listening to Sources, Talking to Sources
• Self Check: Finding Evidence

Writing Process: Organizing

• Outcome: Organizing
• Moving Beyond the Five-Paragraph Theme
• Introduction to Argument
• The Three-Story Thesis
• Organically Structured Arguments
• Logic and Structure
• The Perfect Paragraph
• Introductions and Conclusions
• Self Check: Organizing

Writing Process: Drafting

• Outcome: Drafting
• From Outlining to Drafting
• Flash Drafts
• Self Check: Drafting

Writing Process: Revising

• Outcome: Revising
• Seeking Input from Others
• Responding to Input from Others
• The Art of Re-Seeing
• Higher Order Concerns
• Self Check: Revising

Writing Process: Proofreading

• Outcome: Proofreading
• Lower Order Concerns
• Proofreading Advice
• "Correctness" in Writing
• The Importance of Spelling
• Punctuation Concerns
• Self Check: Proofreading
• Conclusion to Writing Process

Research Process: Finding Sources

• Introduction to Research Process
• Outcome: Finding Sources
• The Research Process
• Finding Sources
• What are Scholarly Articles?
• Finding Scholarly Articles and Using Databases
• Database Searching
• Advanced Search Strategies
• Preliminary Research Strategies
• Reading and Using Scholarly Sources
• Self Check: Finding Sources

Research Process: Source Analysis

• Outcome: Source Analysis
• Evaluating Sources
• CRAAP Analysis
• Evaluating Websites
• Synthesizing Sources
• Self Check: Source Analysis

Research Process: Writing Ethically

• Outcome: Writing Ethically
• Academic Integrity
• Defining Plagiarism
• Avoiding Plagiarism
• Using Sources in Your Writing
• Self Check: Writing Ethically

Research Process: MLA Documentation

• Introduction to MLA Documentation
• Outcome: MLA Documentation
• MLA Document Formatting
• MLA Works Cited
• Creating MLA Citations
• MLA In-Text Citations
• Self Check: MLA Documentation
• Conclusion to Research Process

Grammar: Nouns and Pronouns

• Outcome: Nouns and Pronouns
• Pronoun Cases and Types
• Pronoun Antecedents
• Try It: Nouns and Pronouns
• Self Check: Nouns and Pronouns

Grammar: Verbs

• Outcome: Verbs
• Verb Tenses and Agreement
• Non-Finite Verbs
• Complex Verb Tenses
• Try It: Verbs
• Self Check: Verbs

Grammar: Other Parts of Speech

• Outcome: Other Parts of Speech
• Comparing Adjectives and Adverbs
• Adjectives and Adverbs
• Conjunctions
• Prepositions
• Try It: Other Parts of Speech
• Self Check: Other Parts of Speech

Grammar: Punctuation

• Outcome: Punctuation
• End Punctuation
• Hyphens and Dashes
• Apostrophes and Quotation Marks
• Brackets, Parentheses, and Ellipses
• Semicolons and Colons
• Try It: Punctuation
• Self Check: Punctuation

Grammar: Sentence Structure

• Outcome: Sentence Structure
• Parts of a Sentence
• Common Sentence Structures
• Run-on Sentences
• Sentence Fragments
• Parallel Structure
• Try It: Sentence Structure
• Self Check: Sentence Structure

Grammar: Voice

• Outcome: Voice
• Active and Passive Voice
• Using the Passive Voice
• Conclusion to Grammar
• Try It: Voice
• Self Check: Voice

Success Skills

• Introduction to Success Skills
• Habits for Success
• Critical Thinking
• Time Management
• Writing in College
• Computer-Based Writing
• Conclusion to Success Skills

Defining Grammar

• An Introduction to Punctuation
• Ph.D., Rhetoric and English, University of Georgia
• M.A., Modern English and American Literature, University of Leicester
• B.A., English, State University of New York

Hear the word  glamour  and what comes to mind? Celebrities, most likely, limousines and red carpets, swarms of paparazzi and more money than sense. But, odd as it may sound,  glamour  comes directly from a decidedly less glamorous word; grammar .

During the Middle Ages,  grammar  was often used to describe learning in general, including the magical, occult practices popularly associated with the scholars of the day. People in Scotland pronounced  grammar  as "glam-our," and extended the association to mean magical beauty or enchantment.

In the 19th century, the two versions of the word went their separate ways, so that our study of English grammar today may not be  quite  as glamorous as it used to be.

There are two common definitions of grammar :

• The systematic study and description of a language .
• A set of rules and examples dealing with the syntax and word structures of a language usually intended as an aid to the learning of that language.

Descriptive grammar (definition #1) refers to the structure of a language as it's actually used by speakers and writers. Prescriptive grammar (definition #2) refers to the structure of a language as certain people think it should be used.

Both kinds of grammar are concerned with rules , but in different ways. Specialists in descriptive grammar (called linguists ) study the rules or patterns that underlie our use of words, phrases, clauses, and sentences. On the other hand, prescriptive grammarians (such as most editors and teachers) layout rules about what they believe to be the “correct” or “incorrect” use of language.

Interfacing With Grammar

To illustrate these different approaches, let's consider the word interface . The descriptive grammarian would note, among other things, that the word is made up of a common prefix ( inter- ) and a root word ( face ) and that it’s currently used as both a noun and a verb . The prescriptive grammarian, however, would be more interested in deciding whether or not it is “correct” to use interface as a verb.

Here's how the prescriptive Usage Panel at The American Heritage Dictionary passes judgment on interface :

The Usage Panel has been unable to muster much enthusiasm for the verb. Thirty-seven percent of Panelists accept it when it designates the interaction between people in the sentence The managing editor must interface with a variety of freelance editors and proofreaders . But the percentage drops to 22 when the interaction is between a corporation and the public or between various communities in a city. Many Panelists complain that interface is pretentious and jargony .

Similarly, Bryan A. Garner, author of The Oxford Dictionary of American Usage and Style , dismisses interface as "jargonmongers' talk."

By their nature, all popular style and usage guides are prescriptive, though to varying degrees: some are fairly tolerant of deviations from standard English ; others can be downright cranky. The most irascible critics are sometimes called "the Grammar Police."

Though certainly different in their approaches to language, both kinds of grammar are useful to students.

The Value of Studying Grammar

The study of grammar all by itself won't necessarily make you a better writer. But by gaining a clearer understanding of how our language works, you should also gain greater control over the way you shape words into sentences and sentences into paragraphs. In short, studying grammar may help you become a more effective writer.

Descriptive grammarians generally advise us not to be overly concerned with matters of correctness : language, they say, isn't good or bad; it simply is . As the history of the glamorous word grammar demonstrates, the English language is a living system of communication, a continually evolving affair. Within a generation or two, words and phrases come into fashion and fall out again. Over centuries, word endings and entire sentence structures can change or disappear.

Prescriptive grammarians prefer giving practical advice about using language: straightforward rules to help us avoid making errors. The rules may be over-simplified at times, but they are meant to keep us out of trouble—the kind of trouble that may distract or even confuse our readers.

• The 9 Parts of Speech: Definitions and Examples
• What Is a Phrase? Definition and Examples in Grammar
• Descriptive Grammar
• 10 Types of Grammar (and Counting)
• Generative Grammar: Definition and Examples
• English Grammar: Discussions, Definitions, and Examples
• Definition and Examples of Prescriptive Grammar
• Why Grammar Is a Timeless Subject to Study and Teach
• Traditional Grammar: Definition and Examples
• What is Considered 'Ungrammatical'?
• Transformational Grammar (TG) Definition and Examples
• The Rules of English
• English Grammar
• What Is a Grammatical Error?
• Lexis Definition and Examples
• Definition and Examples of Grammaticality

What is Grammarly?

Grammarly helps people communicate with confidence across devices and platforms. Our AI-powered suggestions appear wherever you write, coaching over 30 million people and 70,000 enterprise and professional teams every day to improve the correctness, clarity, engagement, and delivery of their writing. Grammarly Premium elevates communication for individual students and professionals, and Grammarly for Business drives organizations of all sizes to accelerate business results.

Grammarly team members use advanced machine learning to break new ground in natural language processing that analyzes written sentences to understand context and tone. We operate with a remote-first hybrid work model, meaning we primarily work from home and, as conditions allow, meet for in-person collaboration at our hubs in San Francisco, New York, Seattle, Vancouver, Berlin, and Kyiv, or in a workspace in Kraków. Grammarly is one of Time’s 100 Most Influential Companies, one of Fast Company’s Most Innovative Companies in AI, a member of the Forbes Cloud 100, and one of Inc.’s Best Workplaces.

To learn more, please visit grammarly.com/about and grammarly.com/business . To see the list of our product offerings, please visit this page: Grammarly's product offerings . 

You can create a free account at https://www.grammarly.com/ .

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An introduction to grammar

This page was published over 8 years ago. Please be aware that due to the passage of time, the information provided on this page may be out of date or otherwise inaccurate, and any views or opinions expressed may no longer be relevant. Some technical elements such as audio-visual and interactive media may no longer work. For more detail, see how we deal with older content .

                                                                            Transcript

What is grammar? How does understanding this powerful tool help us to communicate ideas and feelings and generally get things done?

This video looks at how a functional approach to grammar can help us to understand professional practice in a range of contexts, for example call centres, education, journalism and subtitling. It also looks at how computer software can be used to analyse language in context in the real world.

Find out more about the course: Exploring English Grammar

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• Originally published: Thursday, 24 March 2016
• Body text - Copyright: The Open University

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Module 5: Grammar

Introduction to grammar, why is it helpful to identify patterns of academic grammar and punctuation usage.

So what does this have to do with grammar?

Because language is how we connect with others, it’s also the way we often form our opinions about people. When you first meet a new person, the way he speaks (or writes or signs) is likely going to be your first impression of him. What if he used some of these phrases?

• I’ve got y’all’s assignments here.
• I might could climb to the top.
• They’re fixing to go for a hike.

If you heard someone say these (and say them with a drawl), you would assume he is from the South or Texas. You may use this assumption to then apply stereotypes about Southern people and customs to this person as well. This kind of judgement may or may not be fair, but we all make these kind of judgements every day.

You can’t control what other people think about you and your language usage, but you can control how you present yourself in different situations.

Code-Switching

One of the challenges facing college writers is that the language used for academic purposes is quite different in style, shape, and tone than the language we use in other settings: our home lives, our professional lives, our religious lives, our romantic lives.

You might have a feeling that the way you talk or write is “wrong.” That isn’t the case at all! All languages have their appropriate uses and settings. Your grandma would not be happy if you spoke in academic language as you’re sitting around the Thanksgiving dinner table. Likewise, your professors aren’t happy when you bring Thanksgiving dinner conversation styles into written assignments for their classes.

This is the idea of code-switching : that each of use moves between different variations of language in different contexts. Academic language is one variation, and it has a strict set of rules to follow. The rules of academic language will be explored in detail in this section.

About the Videos in this Module

You’ll quickly recognize a distinctive voice and format in the videos in this section of the course.  Our narrator guide will be David, Grammar Content Fellow from the Khan Academy. He offers charming insights and a straightforward, encouraging approach to understanding our language in all its quirks.

Get started with David, and with Grammar, here.

Learning Objectives

By the end of this section, you will be able to

• Identify the function of nouns and different noun types.
• Identify the function and structure of pronouns.
• Identify verb types and their correction conjugation.
• Identify adjectives, adverbs, and the differences between the two.
• Identify the function other parts of speech, including conjunctions, prepositions, and articles.
• Identify common punctuation marks and the rules for their correct usage.
• Identify common sentence types and common errors in sentence composition.
• Identify the active and passive voices, as well as the reasons to use both.
• Why It Matters: Grammar. Provided by : Lumen Learning. License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike
• Conversation Balloons. Authored by : bartek001. Located at : https://pixabay.com/en/conversation-balloons-anger-545621/ . License : CC0: No Rights Reserved
• Code-switching. Authored by : Heather Coffey. Provided by : Learn NC. Located at : http://www.learnnc.org/lp/pages/4558 . License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike
• Introduction to Grammar. Authored by : Khan Academy. Located at : https://youtu.be/O-6q-siuMik . License : All Rights Reserved . License Terms : Standard YouTube License

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• English Grammar

Grammar is  the language system that  allows words to change their form, their order in a sentence, and combine with other words in novel ways .  This applies to both written and spoken language.  In this article, we will look at the main principles of English grammar.                            

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• Everything you need to ace your exams
• 5 Paragraph Essay
• Argumentative Essay
• Cues and Conventions
• Active Voice
• Adjective Phrase
• Adverb Phrase
• Adverbials For Time
• Adverbials of Frequency
• Auxilary Verbs
• Complex Sentence
• Compound Adjectives
• Compound Sentence
• Conditional Sentences
• Conjugation
• Conjunction
• Coordinating Conjunctions
• Copula Verbs
• Correlative Conjunctions
• Dangling Participle
• Declaratives
• Demonstrative Pronouns
• Dependent Clause
• Descriptive Adjectives
• Distributives
• Exclamatives
• Finite Verbs
• First Conditional
• Functions of Language
• Future Progressive Tense
• Future Tense
• Generative Grammar
• Grammatical Mood
• Grammatical Voices
• Imperative Mood
• Imperative Verbs

Imperatives

• Indefinite Pronouns
• Independent Clause
• Indicative Mood
• Infinitive Mood
• Infinitive Phrases
• Interjections
• Interrogative Mood

Interrogatives

• Irregular Verbs
• Linking Verb
• Misplaced Modifiers
• Modal Verbs
• Noun Phrase
• Objective Case
• Optative Mood
• Passive Voice
• Past Perfect Tense
• Perfect Aspect
• Personal Pronouns
• Possessive Adjectives
• Possessive Pronouns
• Potential Mood
• Preposition
• Prepositional Phrase
• Prepositions of Place
• Prepositions of Time
• Present Participle
• Present Perfect Progressive
• Present Perfect Tense
• Present Tense
• Progressive Aspect
• Proper Adjectives
• Quantifiers
• Reflexive Pronouns
• Relative Clause
• Relative Pronouns
• Second Conditional

Sentence Functions

• Simple Future Tense
• Simple Sentence
• Subjunctive Mood
• Subordinating Conjunctions
• Superlative Adjectives
• Third Conditional
• Transitive and Intransitive Verbs
• Types of Phrases

Types of Sentence

• Verb Phrase
• Vocative Case
• Zero Conditional
• English Language Study
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• Essay Writing Skills
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• History of English Language
• International English
• Key Concepts in Language and Linguistics
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• Linguistic Terms
• Listening and Speaking
• Multiple Choice Questions
• Research and Composition
• Rhetorical Analysis Essay
• Single Paragraph Essay
• Sociolinguistics
• Summary Text
• Synthesis Essay
• Textual Analysis

Who makes the rules of English grammar?

If we think for a moment about the origins of the English language (don't worry, this won't take long!), we can see that it has been influenced by many other languages, including French, Latin and Greek. However, English is classed as a Germanic language , as it was heavily influenced by Anglo-Saxon settlers in Britain around the 5th century. This is why the syntax and grammar of English are similar to German.

English grammar was originally influenced by its Germanic ancestry, but who makes the rules now? Well - nobody, and everybody! There is no official regulating body that decides on the rules of English grammar, and like most languages, the rules rely on a general consensus.

I n this article, we will look at the principles of English grammar; knowing these will help improve your communication skills and give you an advantage in your English language studies.

Elements of English grammar

Below we have covered some of the most essential elements of English grammar. Keep in mind that we also have individual articles for each of these elements, which cover the topics in more detail.

The main elements of English grammar we'll be looking at today are: morphemes , clauses, conjunctions, types of phrase, grammatical voice , tenses , aspects , types of sentence , sentence functions , and word classes.

A morpheme is the smallest unit of meaning in a language; t his means it cannot be reduced without losing its meaning.

The word luck is a morpheme as it cannot be made any smaller.

Morphemes are different from syllables, which are units of pronunciation.

There are two types of morphemes: free morphemes and bound morphemes .

Free morphemes

Free morphemes can stand alone . Most words fall into this category, regardless of how long they are . Take the word 'tall' for example - it has a meaning on its own, you can't break it down into smaller parts (such as t-all, ta-ll, or tal-l). ' Ostrich' is also a free morpheme; despite having more than one syllable , it cannot be broken down into smaller parts.

Note that the word 'tall' contains the word 'all', but this has a completely different, unrelated meaning, so 'tall' is still a morpheme. The same principle applies to 'ostrich' - it may have the word 'rich' in it, but this is completely unrelated to the original word, and so 'ostrich' is still a morpheme in its own right.

Free morphemes can be either lexical or functional .

Lexical morphemes give us the main meaning of a sentence or text; they include nouns (e.g. boy, watermelon ), adjectives (e.g. tiny, grey ), and verbs (e.g. run, parachute ).

Functional morphemes help to hold the structure of a sentence together; they include prepositions (e.g. with, by, for ), conjunctions (e.g. and, but ), articles (e.g. the, a, an ) and auxiliary verbs ( e.g. am, is, are ).

In the phrase, 'The tiny boy is running.'

The lexical morphemes are 'tiny', 'boy', and running', and the functional morphemes are 'the', and 'is'.

Bound morphemes

Bound morphemes cannot stand alone and have to be bound to another morpheme.

Bound morphemes include prefixes, like pre-, un-, dis- (e.g. pre recorded, un divided) , and suffixes, like -er, -ing, -est (e.g. small er , smil ing , wid est ).

Prefixes and suffixes both come under the category of 'affixes'.

Two major clause types

Clauses are the building blocks of sentences. Clauses contain a subject (a person, place, or thing) and a predicate (the part of the sentence that contains a verb or information about the subject).

In English, there are two major clause types; independent clauses and dependent clauses .

Independent clauses

An independent clause (also called the main clause) is part of a sentence that works on its own - it can be a complete sentence without any additions.

Examples of independent clauses:

Simon started crying.

We will have some dessert.

Merle lives in a small town.

Dependent clauses

Dependent clauses (also known as subordinate clauses) do not form a complete sentence on their own -they have to be added to independent clauses to make grammatical sense.

Examples of dependent clauses:

When he broke his leg.

After the main course.

Where it's always sunny.

Now let's put the independent clauses and the dependent clauses together:

As you can see, the independent clauses make sense on their own and with the dependent clauses added. The dependent clauses do not make sense unless they are attached to an independent clause.

Conjunctions

Conjunctions are words that “conjoin” or “connect” words, clauses, or phrases. They are an important grammatical tool as they help to form longer, more complex sentences, with simple sentences.

Thanks to conjunctions, the short, simple sentences 'I sing', 'I play the piano', and ' I don't play the guitar ' can become one longer, more complex sentence : ' I sing and I play the piano but I don't play the guitar' . The conjunctions ' and' and 'but' connect the shorter sentences.

There are three types of conjunction , each used for different purposes: coordinating conjunctions , subordinating conjunctions , and correlating conjunctions .

Coordinating conjunctions

Coordinating conjunctions join two parts of a sentence that have equal meaning or are equal in importance . This could be two words or two clauses (see the previous section for more on clauses).

There are seven coordinating conjunctions in English. An easy way to remember them is with the acronym ' FANBOYS' :

Olivia has three rabbits and ten fish.

Ben didn't want to speak to his parents or his grandparents.

I love roast dinners but I can't stand sprouts.

Subordinating conjunctions

Subordinating conjunctions join two parts of a sentence that have unequal meanings . In other words, t hey join an independent clause to a dependent clause (again, see the section above on clauses if you're not sure what this means).

Subordinating conjunctions are used to show cause and effect, a contrast, or a relationship of time/place between clauses.

Examples of subordinating conjunctions:

Peter didn't leave the house due to the tiger in his front garden.

Peter is going to the bakery if the tiger leaves his garden.

The tiger has been there since midday.

Correlating conjunctions

Correlating conjunctions are two conjunctions that work together in a sentence ; they are also known as paired conjunctions .

Examples of correlating conjunctions:

I'm going to eat either soup or casserole for dinner.

Mia was not only rude but also quite mean.

My mum is taking both my sister and me to the beach.

Types of phrase

A phrase is a group of interrelated words that can function on its own, or as part of a sentence or clause . A phrase is different from a clause because it does not require a subject and a predicate (see our section on clauses for more information on this).

There are five different types of phrase: noun phrase , adjective phrase , verb phrase , prepositional phrase and adverb phrase .

Let's take a look at them now.

Noun phrase

A noun phrase functions as a noun ; it consists of the noun and its modifiers and/or determiners.

Modifiers - An optional word which gives more meaning to a noun, pronoun , or verb .

Determiners - Words used in front of nouns to show when you are referring to something specific. They add information regarding quantity, ownership, and specificity.

The small brown dog was yapping.

I work in the city centre library .

Look at that massive fish !

Adjective phrase

An adjective phrase functions as an adjective , meaning that it modifies (i.e. gives more information about) a noun or pronoun . An adjective phrase consists of the adjective and its modifiers and/or determiners.

The film was very short .

This section contains some absolutely fascinating books.

Bill is even stronger than all of the boys in his class

Verb phrase

A verb phrase functions as a verb ; it contains a verb and any auxiliary verbs (e.g. be, have, do ), plus any modifiers and/or determiners.

I am waiting for my big day to come.

She has written a lot of books.

The show will be starting soon.

Prepositional phrase

A prepositional phrase contains a preposition and its object, along with any modifiers and/or determiners .

The cow jumped over the moon .

Her shoes were inside the wardrobe .

We ventured into the briny deep .

Adverb phrase

An adverb phrase (sometimes known as an adverbial phrase) f unctions as (you guessed it) an adverb . An adverb phrase explains how, why, where, or when a verb is done.

They stirred the stew with a wooden spoon .

He finished the exam at record speed .

Every day I feed the ducks.

Grammatical Voice

In English, there are two types of grammatical voice : the active voice and the passive voice .

The active voice is much more common - in the active voice , the subject does the action . In the passive voice , the subject is acted upon .

Compare the sentences below and note how the active voice draws attention to the doer of an action , whereas the passive voice draws attention to the thing being acted upon . The thing being acted upon is known as the object.

The subject is the focus of a sentence - it is what (or who) the sentence is about. In the sentence 'Jenny ate a pizza', Jenny is the subject , and the pizza is the object . In the sentence 'The pizza was eaten by Jenny', the pizza is the subject .

Tenses tell us whether something is in the past, present or future . See the table below for a comparison of the three main tenses.

Some linguists argue that the future isn't technically a 'tense' in English; however, it is now commonly taught as tense and it's helpful to put it here so you can see how the verb moves from past to future.

All of the examples above are the "simple" versions of each tense. There are a total of four versions of each tense, creating twelve different tenses - to find out more, read the following section on aspects .

Aspects give us additional information about a verb by telling us whether an action has been completed, is continuous, is both, or is neither . Aspects work together with tenses to add precision.

The two main aspects are progressive and perfective . We will look at examples of each one, and see what happens when we pair them with different tenses.

Progressive

The progressive aspect (also called the continuous aspect) tells us that the verb or action is, was, or will be, continuous.

Examples of the progressive aspect :

You can describe verbs or actions as continuous regardless of whether they are in the past, present or future. For example, compare the simple past tense of ' The girl ate chocolate ' to the past progressive tense of ' The girl was eating chocolate '. To say the girl ' was eating ' suggests that the action occurred over a period of time, and so it was continuous.

The perfective aspect tells us that the verb or action is either complete, will be complete, or will have been continuous up to a certain point.

Examples of the perfect aspect :

As you can see, the perfective aspect can tell us that an action is complete , e.g. the present perfect tense ' I have cooked past a', or it can tell us that it will be complete , such as the future perfect tense of 'I will have cooked pasta'.

The perfective aspect can also tell us that an action has been continuous up to a certain point e.g. ' I have lived in Tokyo for ten years ' (an example of the present perfect tense) tells you how long I have lived in Tokyo, up to the present moment . Similarly, the phrase ' Next week, I will have lived in Tokyo for eleven years ' (an example of the future perfect tense) tells you how long I will have lived in Tokyo at a point in the future (in this case , next week).

The twelve tenses

When we pair up aspects with tenses, we get a total of twelve tenses ; these tell us whether an action is in the past, present or future, along with its “status” (whether it is continuing or completed). Below is a list of all twelve tenses with examples:

There are four main types of sentences.

Simple sentences

Compound sentences, complex sentences, compound-complex sentences.

You can spot the sentence type by looking at the clauses .

Simple sentences usually communicate things clearly. The sentences do not need added information as they work well on their own, and t hey consist of a single independent clause .

• James waited for the bus.

I looked for Mary at the park.

We all walked to the shop.

Simple sentences usually communicate things clearly. The sentences do not need added information as they work well on their own; they consist of a single independent clause .

Compound sentences combine two or more independent clauses , joining them with a comma, semicolon, or coordinating conjunction (see our section on conjunctions for more information on what these are).

Like simple sentences, compound sentences do not include dependent clauses (clauses that rely on the rest of the sentence). If the link (e.g. a comma or conjunction) between the two (or more) independent clauses weren't there, they could both work independently as simple sentences.

I need to go to work but I am too sick to drive.

He ran out of money so he couldn't buy lunch.

The sun is shining and the air is fresh.

Complex sentences are slightly different from the other two types of sentences as they include a dependent clause (also known as a subordinate clause).

They are formed by adding dependent clauses to an independent clause. The dependent clauses are either joined to the main (independent) clause through subordinating conjunctions or relative pronouns .

The relative pronouns are that, which, who, whose, whom, and whomever.

I heated my food in the microwave because it had gone cold.

Amy sent back her item after she realized it was damaged.

I tried to get the attention of the cashier whose wig had fallen off.

This type of sentence combines a compound sentence with a complex sentence .

Compound-complex sentences contain two (or more) independent clauses as well as at least one dependent clause . Because of this, they are usually the longest sentence type, as they include a lot of clauses.

Since leaving school , I have been working in an office and I am saving up to buy a car.

I was thirsty so I went to the fridge to grab a can of soda.

Peter waited patiently until after midnight, but the tiger refused to budge.

Sentence functions describe the purpose of a sentence. There are four main sentence functions in the English language: declarative , interrogative , imperative , and exclamative .

Declarative

Declarative sentences are the most common. We use declarative sentences to:

Make a statement.

Give an opinion.

Provide an explanation.

State facts.

I love hiking.

It's cold because he left the windows open.

The capital of Kenya is Nairobi.

Interrogative sentences are used to ask questions and typically require an answer. Here are the different types of interrogative sentences along with examples:

Yes / No interrogatives e.g. ' Have you ever been to India?'

Alternative interrogatives (questions that offer two or more alternative answers) e.g. ' Would you like tea or coffee?'

WH-interrogative (who / what / where / why / how) e.g. ' Where is the post office?'

Negative interrogatives (a question that has been made negative by adding a word such as not, don't aren't and isn't ) e.g. ' Why aren't you in bed?'

Tag questions (short questions tagged onto the end of a declarative sentence) e.g. ' We forgot the milk, didn't we?'

Imperative sentences are predominantly used to give a command or a make a demand. They can be presented in several ways, such as:

Giving instructions.

Offering advice.

Making a wish on behalf of someone else.

Extending an invitation.

Giving a command.

There is often no subject present when forming imperative sentences because the subject is assumed to be you - the reader or the listener.

Set the oven to 180 degrees.

Please, take a seat.

Exclamative

Exclamative sentences are used to express strong feelings and opinions , such as surprise, excitement, and anger. A true e xclamative sentence should contain the words what or how and usually end with an exclamation mark (!).

What a nice surprise!

Oh, how lovely!

What's that?!

Exclamative sentences help us to express strong feelings

Word Classes

Word classes help us to better understand the elements that form phrases and sentences.

There are four main word classes: nouns, verbs, adjectives, and adverbs . These are considered lexical word classes and they provide the most meaning in a sentence.

The other five word classes are prepositions, pronouns, determiners, conjunctions, and interjections . These are functional word classes ; they give structure to sentences by "glueing" them together, and they also show the relationships between lexical items.

See below for a summary of each word class , along with examples.

Lexical word classes

Here is a table containing the lexical word classes.

Functional word classes

Here is a table containing the functional word classes.

English Grammar - Key takeaways

• A morpheme is the smallest unit of meaning in a language. I t cannot be reduced beyond its current state without losing its meaning.
• Clauses contain a subject and a predicate. In English, there are two major clause types: independent clauses and dependent clauses.
• Conjunctions are words that connect two words, clauses, or phrases. They help to form longer, more complex sentences from simple sentences.
• A phrase is a group of interrelated words that can function alone, or as part of a sentence or clause . Phrases differ from clauses because they don't require a subject and predicate .
• There are two types of grammatical voice : the active voice and the passive voice.
• Tenses give us a sense of time by telling us whether something is in the past, present or future .
• Aspects give us additional information about a verb by telling us whether an action has been completed, is continuous, is both, or is neither . Aspects work together with tenses.
• There are four different types of sentences : simple, compound, complex, and compound-complex.
• There are four main sentence functions: declarative , interrogative , imperative , and exclamative .
• The four main word classes are nouns, adjectives, verbs, and adverbs . These are lexical classes that give meaning to a sentence. The other five word classes are prepositions, pronouns, determiners, conjunctions, and interjections . These are function classes that are used for grammatical or structural reasons.

Flashcards in English Grammar 1829

What are the three main tenses?

Past tense, Present tense, and Future tense.

 Which one of the following is a verb tense?

Perfect past tense.

Continuing past tense. 

Which of the following is an example of present tense?

We walked to the shops.

I am running.

I’m going to go for a walk.

What tense shows something will happen?

Future tense.

Which word type commonly shows tense?

What are the two most common tenses?

Past and present.

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Frequently Asked Questions about English Grammar

What are grammatical rules?

Grammar is the system that allows words to change their form, their order in a sentence, and combine with other words in novel ways – this applies to both written and spoken language.

What are the basic rules of grammar?

The basic rules of grammar depend on the correct use of:

Grammatical voice

Types of sentence

Sentence functions

Confused? Don’t worry, StudySmarter has detailed articles to help clarify each of these rules.

What are the 12 types of tenses?

The 12 tenses are:

Simple past

Past perfect

Past progressive

Past perfect progressive

Simple present

Present perfect

Present progressive

Present perfect progressive

Simple future

Future perfect

Future progressive

Present future progressive

For more information, see our article on tenses.

What are five examples of compound sentences?

Five examples of compound sentences are:

He ran out of money so he couldn’t buy lunch.

Everybody listen to me; we need to pull together as a team!

She loves to go swimming; staying healthy is important to her. 

What are the two types of clause?

The two types of clauses in English are: independent clauses (clauses that can stand alone) and dependent clauses (clauses that need to be attached to an independent clause to make grammatical sense). For more information, see our article on clauses.

Test your knowledge with multiple choice flashcards

Which of the following best describes the present perfect continuous/progressive tense?

Which of the following is an example of a proper noun?

Pick out the concrete noun from the following:

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Teaching Grammar Introduction: What is Grammar?

• Teaching Grammar
• January 24, 2021

What is Grammar?

Grammar is the structural ‘rules’ of a language. It covers:

• Syntax : the order in which words and phrases are ordered to create meaningful expressions in a language
• Morphology : word forms and the formation of words by the addition of prefixes and suffixes
• Semantics : the meaning of a language

-Is Your CELTA Certification Course Missing Grammar ?-

What do Teachers Need to Consider?

When teachers are introducing a new grammar point, they need to be aware of the whole range of features that make up the grammar.  Teachers need to think about when and how a language structure is used.

A thorough presentation of a grammar point needs to address:

• the meaning that is expressed by the structure
• the form that the structure takes

In addition, teachers need to think about pronunciation : how do students say the new structure?

Teachers also need to recognize that sometimes common usage in English can be somewhat different than what is specified in many grammar texts. Languages are constantly changing and evolving, so sometimes general usage may conflict with what grammar books describe.

Analyzing Language Before Teaching

Before teaching a grammar point, teachers need to thoroughly analyze the features of the new language. It is important to have a clear understanding of the key concepts and meanings expressed by a structure.

It is not good enough to say, for example, that a structure expresses ‘future’. There are many different ways of expressing the future in English: how is one structure different from another?

Teachers need to consider the contexts in which a structure is used, and which meanings of a structure are appropriate for different levels.

Present simple, for example, is taught to low beginners to express daily habits and routines, but it can also be used in past tense narratives  (in some storytelling contexts) which is a usage that is more appropriate for higher levels.

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Teaching Grammar Communicatively (VIDEO)

Teaching Grammar Using the Communicative Approach

Information Gaps: Teaching Grammar and Speaking Skills Activity

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IELTS Speaking Topics Part 1, 2 and 3

Explore the latest IELTS Speaking topics with answers for Part 1, Part 2, and Part 3. Find IELTS Speaking questions and answers to excel in your test.

The International English Language Testing System (IELTS) Speaking test assesses a candidate's ability to communicate effectively in English. As part of the test, candidates are expected to engage in a conversation with an examiner on a range of topics. These topics, known as common IELTS Speaking topics , cover various aspects of everyday life, personal experiences, social issues, and global trends. By exploring these topics, candidates can showcase their language skills, fluency, vocabulary, and ability to express their thoughts and opinions in a coherent manner. This diverse set of topics enables candidates to demonstrate their proficiency in English and provides a comprehensive assessment of their speaking abilities.

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What is the IELTS Speaking test format?

The Speaking test format remains consistent for both the Academic and General Training versions of the IELTS examination. Whether taking the test on a computer or in person, the Speaking test maintains its face-to-face nature, allowing candidates to directly interact with a certified IELTS examiner.

The duration of the Speaking test remains unchanged, with a time frame of 11 to 14 minutes allotted for both the Academic and General Training tests. This standardised approach ensures a fair and reliable assessment of candidates' speaking abilities across all test formats.

Learn about IELTS Speaking part 1, 2 and 3

There are three parts to a Speaking Test:

Part 1: (4–5 minutes) Introduction and interview. The IELTS examiner will introduce him/herself and will ask you to also introduce yourself, besides confirming your identity. The examiner will ask you generic questions on topics like family, studies, work, and your interests.

Part 2: (3–4 minutes) Individual long turn. The examiner will give you a task card with a topic written on it, with some points you may cover in your speech. You will have one minute to think and prepare upon the topic; a paper and pencil will be provided to jot down your notes. Once done ideating, you will have a time of one to two minutes to speak on the subject followed by some questions on the same by the examiner.

Part 3: (4–5 minutes) Two-way discussion. The examiner will ask more questions related to the topic provided in Part 2 of the Speaking test. You can use this opportunity to talk about more ideas.

Latest IELTS Speaking topics

Here are some common IELTS Speaking topics that often come up in the test:

1. Personal information:

Introduce yourself (name, occupation, where you're from)

Talk about your family

Describe your hometown

2. Hobbies and interests:

Discuss your favourite leisure activities

Talk about sports you enjoy or follow

Share your hobbies and why you like them

3. Education and work:

Describe your current or past studies

Talk about your job or future career plans

Discuss your favourite subjects and why you like them

4. Travel and tourism:

Describe a memorable trip you've taken

Talk about a place you would like to visit and why

Discuss the importance of travel and its benefits

5. Technology and media:

Talk about your favourite websites or apps

Discuss the influence of social media

Share your opinion on the advantages and disadvantages of technology

6. Environment and conservation:

Discuss environmental issues and their impact

Talk about steps to protect the environment

Share your opinion on sustainable living

7. Health and fitness:

Discuss the importance of a healthy lifestyle

Talk about your exercise routine or favourite sport

Share your opinion on junk food and its effects

8. Culture and traditions:

Talk about a traditional festival in your country

Discuss the importance of preserving cultural heritage

Share your opinion on globalisation and its impact on culture

9. Social issues:

Discuss poverty and its causes.

Talk about the impact of immigration on society.

Share your opinion on gender equality.

10. Future plans and aspirations:

Talk about your goals and ambitions

Discuss your plans for further education

Share your opinion on the importance of setting goals

Remember, these are just some common topics, and the actual questions may vary. It's essential to practice speaking about a wide range of subjects to be well-prepared for the IELTS Speaking test .

IELTS Speaking topics: Questions with answers

Here are some common IELTS Speaking topics along with sample answers for all three parts:

Part 1: Introduction and General questions

Ques:: What's your name?

Ans: My full name is John Smith.

Ques: Can I see your ID?

Ans: Sure, here's my passport.

Ques: Where are you from?

Ans: I'm from London, England.

Ques: Do you work or study?

Ans: I work as a software engineer in a tech company.

Ques: What do you like to do in your free time?

Ans: In my free time, I enjoy reading books and playing the guitar.

Part 2: Cue card (Describe a specific topic)

Ques: Talk about a person who has inspired you.

Ans: One person who has been a great source of inspiration for me is my grandmother. She has overcome numerous challenges in her life and has always maintained a positive attitude. Her resilience and determination have taught me the value of perseverance. She has also instilled in me the importance of kindness and empathy towards others. Whenever I face difficulties, I think of her strength, and it motivates me to keep pushing forward.

Part 3: Discussion and follow-up questions

Ques: How important is it to travel and experience different cultures?

Ans: Traveling and experiencing different cultures is highly important as it broadens our perspectives and deepens our understanding of the world. It allows us to appreciate diversity, learn from different traditions, and break down stereotypes. Moreover, it fosters cultural exchange and promotes mutual respect among people from different backgrounds. Overall, traveling enriches our lives and contributes to personal growth.

Ques: What are the benefits of learning a foreign language?

Ans: Learning a foreign language has numerous benefits. Firstly, it improves communication skills and enables effective interaction with people from different cultures. Secondly, it enhances cognitive abilities, such as memory and problem-solving. Additionally, it opens up job opportunities in an increasingly globalised world. Lastly, learning a foreign language promotes cultural appreciation and fosters a deeper understanding of other societies. It's a valuable skill that broadens horizons and enriches personal development. Remember to personalise your answers and provide specific examples from your own experiences whenever possible. Practice speaking aloud and focus on fluency, coherence, and accuracy. Good luck with your IELTS preparation !

Studying different IELTS topics for the Speaking test helps you build vocabulary, develop ideas, enhance fluency and coherence, and increase your preparedness for a variety of subjects. It is an effective strategy to improve your performance and increase your chances of achieving a higher score on the IELTS Speaking test .

Why should you study different IELTS topics for the Speaking test?

Studying different IELTS topics for the Speaking test is beneficial for several reasons:

Familiarity with a range of topics

The Speaking test in IELTS covers a wide range of topics, including personal experiences, education, work, society, culture, and current affairs. By studying different topics, you become familiar with the vocabulary, ideas, and concepts related to each one. This helps you feel more confident and prepared when discussing these topics during the test.

Vocabulary expansion

Each topic has its own specific vocabulary and terminology. By studying different IELTS topics, you expose yourself to a variety of vocabulary words and phrases related to various subject areas. This expands your overall vocabulary, enabling you to express yourself more effectively and precisely during the Speaking test.

Development of ideas and opinions

Studying different topics allows you to develop ideas and opinions on a wide range of subjects. This is crucial because the Speaking test evaluates your ability to express your thoughts and provide relevant examples. By exploring different topics, you enhance your critical thinking skills, enabling you to generate well-structured responses during the test.

Enhanced fluency and coherence

The Speaking test assesses your ability to speak fluently and coherently. When you study different topics, you expose yourself to diverse content, which helps improve your fluency and coherence. Regular practice discussing various topics helps you organise your thoughts quickly and express them in a coherent manner, leading to a higher score on the Speaking test.

Preparedness for unexpected topics

While there are common IELTS topics that often appear in the Speaking test, there is always a chance of encountering unexpected or less familiar topics. By studying a wide range of topics, you develop the ability to adapt quickly and discuss unfamiliar subjects with confidence. This flexibility enhances your performance and ensures you are well-prepared for any topic that may arise during the test.

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Living Cost in Australia for International Students

IELTS Writing Task 2 Essay: Topics, Samples and Tips to Score Band 9!

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IELTS announces at-home testing option

7 myths about the IELTS Writing test to dispel

IELTS Speaking: AI vs face-to-face speaking with an examiner

3 parts of IELTS Speaking, and what to look out for!

Don’t overthink during your IELTS test - 7 tips you must know!

Don't overdo it: How to ace your IELTS Speaking test

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Python vs R: Which Language Excels in Data Analysis?

Introduction

Data is the lifeblood of your organization, so the ability to analyze and interpret data effectively is crucial to your success. Across industries, organizations rely on data analysis to make informed decisions, optimize processes, and gain a competitive edge. Python and R are two of the most popular programming languages among the many tools and methods available for data analysis. We will compare Python and R in this blog to help you understand their core strengths, use cases, and how to choose the right tool for your specific needs.

Background of Python and R

History and development of python.

Python, created by Guido van Rossum and first released in 1991, is a high-level, general-purpose programming language. Known for its simplicity and readability, Python has become a favorite among developers and data scientists alike. Its design philosophy emphasizes code readability and syntax that allow programmers to express concepts in fewer lines of code. Python's extensive standard library and vibrant community have contributed to its widespread adoption and continuous growth.

History and Development of R

Statisticians Ross Ihaka and Robert Gentleman created R in the early 1990s. It was designed specifically for statistical computing and graphics, making it an ideal data analysis and visualization tool. R is an implementation of the S programming language and strongly focuses on providing a variety of statistical techniques, including linear and nonlinear modeling, time-series analysis, and clustering. Over the years, R has garnered an active community of statisticians and data scientists who have contributed numerous packages to extend its capabilities.

Popularity and Community Support

Python and R boast large communities providing extensive support and resources. Python's versatility has made it popular in various domains beyond data analysis, such as web development, automation, and machine learning. It has resulted in a diverse community with many tutorials, forums, and libraries. R's community, while more specialized, is highly focused on statistical analysis and data visualization. The Comprehensive R Archive Network (CRAN) hosts thousands of packages contributed by users, ensuring that R remains a powerful tool for data analysis.

Core Strengths of Python

Versatility and ease of learning.

One of Python's greatest strengths is its versatility. Its simple and intuitive syntax makes it an excellent choice for beginners and experienced programmers. The language's readability and straightforward learning curve allow users to quickly pick up and start coding, making it a popular choice for introductory programming courses.

Extensive Libraries

Python has extensive libraries that are invaluable for data analysis. Some of the most widely used libraries include:

Integration with Other Languages and Tools

Python's ability to integrate with other languages and tools further enhances its appeal. It can be easily combined with languages like C, C++, and Java, as well as tools such as Hadoop and Spark, making it a powerful component in a data scientist's toolkit. Python's compatibility with various databases and its ability to handle web scraping, data cleaning, and automation tasks add to its versatility.

Use Cases in Web Development, Machine Learning, and Automation

Python's application extends beyond data analysis into web development, with frameworks like Django and Flask enabling the creation of robust web applications. Thanks to libraries like TensorFlow, Keras, and Scikit-learn, Python is the go-to language in machine learning. Additionally, Python's ability to automate repetitive tasks makes it a valuable tool for improving workflow efficiency and productivity.

Core Strengths of R

Designed specifically for statistical analysis and data visualization.

R's primary strength lies in its design for statistical analysis and data visualization. Its syntax and functions can perform complex statistical operations and produce high-quality plots with minimal effort, making R an excellent choice for statisticians and data scientists focused on data exploration and presentation.

Powerful Packages

R has extensive libraries that help better analyze data. Some of the most widely used libraries include:

Strong Capabilities in Exploratory Data Analysis

R's strong capabilities in exploratory data analysis (EDA) make it a preferred tool for initial data exploration and hypothesis testing. Functions for summary statistics, data visualization, and data cleaning are readily available, allowing users to gain insights and identify patterns in their data quickly.

Use Cases in Academic Research and Data Science

Because of its many capabilities, R is used extensively in academic research and data science. Researchers across various disciplines rely on R to analyze experimental data, conduct statistical tests, and visualize results. Its extensive library ecosystem ensures that users have access to powerful techniques and methodologies for their analyses.

Comparing Python and R in Data Analysis

Data manipulation and cleaning.

Python and R excel in data manipulation and cleaning but approach it differently. Python's Pandas library offers a powerful and flexible framework for handling structured data, with functions for merging, reshaping, and aggregating datasets. R's dplyr package provides similar functionality with an intuitive syntax allowing users to chain multiple operations.

Data Visualization Capabilities

In data visualization, R's ggplot2 is often considered superior due to its flexibility and the quality of its plots. However, Python's Matplotlib and Seaborn libraries are also highly capable and widely used. While ggplot2's grammar of graphics approach allows for highly customized plots, Matplotlib and Seaborn offer more straightforward options for creating standard visualizations.

Machine Learning and Advanced Analytics

Thanks to its extensive libraries and frameworks, Python has a clear edge in machine learning and advanced analytics. TensorFlow, Keras, and Scikit-learn provide comprehensive tools for building and deploying machine learning models. While R also has packages for machine learning, such as caret and randomForest, Python's ecosystem is more mature and widely adopted in the industry.

Performance and Scalability

Performance and scalability are crucial considerations for large-scale data analysis. You can enhance Python's performance through libraries like NumPy, which leverage optimized C and Fortran code. Additionally, Python's ability to integrate with big data tools like Hadoop and Spark makes it suitable for handling large datasets. R, while efficient for smaller datasets, may require additional packages like data.table for improved performance with larger datasets.

Ease of Use and Learning Curve

Python's simple syntax and readability make it easier to learn and use, especially for those with a programming background. While a powerful tool for statistical analysis, R's syntax can be less intuitive for beginners. However, R's domain-specific design can benefit those primarily focused on statistical analysis and visualization.

Choosing the Right Tool for Your Needs

When choosing between Python and R, consider project requirements, existing skill sets, and team preferences. Python's versatility makes it a strong candidate if your project involves a mix of data analysis, web development, and machine learning. R's specialized capabilities may be more suitable if the focus is on statistical analysis and data visualization.

Scenarios Where Python is More Suitable

• Projects that require integration with web applications or other programming languages
• Machine learning and artificial intelligence applications
• Automation of repetitive tasks
• Development of scalable solutions for large datasets

Scenarios Where R is More Suitable

• Academic research with a strong emphasis on statistical analysis
• Projects that require advanced data visualization
• Exploratory data analysis with complex statistical techniques
• Workflows that benefit from R's extensive package ecosystem for statistical computing

In conclusion, Python and R are powerful data analysis tools with unique strengths. Python's versatility, extensive libraries, and integration capabilities make it an excellent choice for various applications, from web development to machine learning. R's design for statistical analysis and data visualization, along with its powerful packages, make it a preferred tool for data scientists and researchers focused on data exploration and presentation. When choosing between the two, consider your specific project requirements, existing skill set, and team preferences to select the language that best fits your needs. As the field of data analysis continues to evolve, both Python and R will remain indispensable tools for extracting valuable insights from data.

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• Interview Problems on Recursion
• Practice Recursion
• MCQs on Recursion
• Recursion Tutorial
• Recursive Function
• Recursion vs Iteration
• Types of Recursions
• Tail Recursion
• Josephus Problem
• Tower of Hanoi
• Check Palindrome

Introduction to Recursion

• What is Recursion?
• Difference between Recursion and Iteration
• Finite and Infinite Recursion with examples
• What is Tail Recursion
• What is Implicit recursion?
• Why is Tail Recursion optimization faster than normal Recursion?
• Recursive Functions
• Difference Between Recursion and Induction

Recursion in different languages

• Recursion in Python
• Recursion in Java
• Recursion in C#
• How to Understand Recursion in JavaScript ?

Standard Problems on Recursion

• Program for Tower of Hanoi Algorithm
• Time Complexity Analysis | Tower Of Hanoi (Recursion)
• Find the value of a number raised to its reverse
• Recursively remove all adjacent duplicates
• Print 1 to n without using loops
• Print N to 1 without loop
• Sort the Queue using Recursion
• Reversing a queue using recursion
• Mean of array using recursion
• Binary to Gray code using recursion
• Sum of natural numbers using recursion
• Delete a linked list using recursion
• Product of 2 Numbers using Recursion
• Decimal to binary number using recursion
• Sum of array elements using recursion
• How to Sort a Stack using Recursion
• Reverse a Doubly linked list using recursion
• Programs for Printing Pyramid Patterns using Recursion
• DFS traversal of a Tree
• Length of longest palindromic sub-string : Recursion
• Count Set-bits of number using Recursion
• Print reverse of a string using recursion
• Print Fibonacci Series in reverse order using Recursion
• Java Program to Reverse a Sentence Using Recursion
• Program for length of a string using recursion
• Sum of digit of a number using recursion
• Program to calculate value of nCr using Recursion
• Find geometric sum of the series using recursion
• Bottom View of a Binary Tree using Recursion
• Convert a String to an Integer using Recursion
• Tail recursion to calculate sum of array elements.

Practice Sets on Recursion

• Recursive Practice Problems with Solutions
• Practice Questions for Recursion | Set 1
• Practice Questions for Recursion | Set 2
• Practice Questions for Recursion | Set 3
• Practice Questions for Recursion | Set 4
• Practice Questions for Recursion | Set 5
• Practice Questions for Recursion | Set 6
• Practice Questions for Recursion | Set 7
• Practice questions for Linked List and Recursion
• Top MCQs on Recursion Algorithm with Answers

What is Recursion?   The process in which a function calls itself directly or indirectly is called recursion and the corresponding function is called a recursive function. Using a recursive algorithm, certain problems can be solved quite easily. Examples of such problems are Towers of Hanoi (TOH) , Inorder/Preorder/Postorder Tree Traversals , DFS of Graph , etc. A recursive function solves a particular problem by calling a copy of itself and solving smaller subproblems of the original problems. Many more recursive calls can be generated as and when required. It is essential to know that we should provide a certain case in order to terminate this recursion process. So we can say that every time the function calls itself with a simpler version of the original problem.

Need of Recursion

Recursion is an amazing technique with the help of which we can reduce the length of our code and make it easier to read and write. It has certain advantages over the iteration technique which will be discussed later. A task that can be defined with its similar subtask, recursion is one of the best solutions for it. For example; The Factorial of a number.

Properties of Recursion:

• Performing the same operations multiple times with different inputs.
• In every step, we try smaller inputs to make the problem smaller.
• Base condition is needed to stop the recursion otherwise infinite loop will occur.

Algorithm: Steps

A Mathematical Interpretation

Let us consider a problem that a programmer has to determine the sum of first n natural numbers, there are several ways of doing that but the simplest approach is simply to add the numbers starting from 1 to n. So the function simply looks like this,

approach(1) – Simply adding one by one f(n) = 1 + 2 + 3 +……..+ n

but there is another mathematical approach of representing this,

approach(2) – Recursive adding  f(n) = 1                  n=1 f(n) = n + f(n-1)    n>1

There is a simple difference between the approach (1) and approach(2) and that is in approach(2) the function “ f( ) ” itself is being called inside the function, so this phenomenon is named recursion, and the function containing recursion is called recursive function, at the end, this is a great tool in the hand of the programmers to code some problems in a lot easier and efficient way.

How are recursive functions stored in memory?

Recursion uses more memory, because the recursive function adds to the stack with each recursive call, and keeps the values there until the call is finished. The recursive function uses LIFO (LAST IN FIRST OUT) Structure just like the stack data structure. https://www.geeksforgeeks.org/stack-data-structure/  

What is the base condition in recursion?   In the recursive program, the solution to the base case is provided and the solution to the bigger problem is expressed in terms of smaller problems.   

In the above example, the base case for n < = 1 is defined and the larger value of a number can be solved by converting to a smaller one till the base case is reached.

How a particular problem is solved using recursion?   The idea is to represent a problem in terms of one or more smaller problems, and add one or more base conditions that stop the recursion. For example, we compute factorial n if we know the factorial of (n-1). The base case for factorial would be n = 0. We return 1 when n = 0. 

Why Stack Overflow error occurs in recursion?   If the base case is not reached or not defined, then the stack overflow problem may arise. Let us take an example to understand this.

If fact(10) is called, it will call fact(9), fact(8), fact(7), and so on but the number will never reach 100. So, the base case is not reached. If the memory is exhausted by these functions on the stack, it will cause a stack overflow error. 

What is the difference between direct and indirect recursion?   A function fun is called direct recursive if it calls the same function fun. A function fun is called indirect recursive if it calls another function say fun_new and fun_new calls fun directly or indirectly. The difference between direct and indirect recursion has been illustrated in Table 1. 

What is the difference between tailed and non-tailed recursion?   A recursive function is tail recursive when a recursive call is the last thing executed by the function. Please refer tail recursion article for details. 

How memory is allocated to different function calls in recursion?   When any function is called from main(), the memory is allocated to it on the stack. A recursive function calls itself, the memory for a called function is allocated on top of memory allocated to the calling function and a different copy of local variables is created for each function call. When the base case is reached, the function returns its value to the function by whom it is called and memory is de-allocated and the process continues. Let us take the example of how recursion works by taking a simple function. 

Time Complexity: O(1) Auxiliary Space: O(1)

When printFun(3) is called from main(), memory is allocated to printFun(3) and a local variable test is initialized to 3 and statement 1 to 4 are pushed on the stack as shown in below diagram. It first prints ‘3’. In statement 2, printFun(2) is called and memory is allocated to printFun(2) and a local variable test is initialized to 2 and statement 1 to 4 are pushed into the stack. Similarly, printFun(2) calls printFun(1) and printFun(1) calls printFun(0) . printFun(0) goes to if statement and it return to printFun(1) . The remaining statements of printFun(1) are executed and it returns to printFun(2) and so on. In the output, values from 3 to 1 are printed and then 1 to 3 are printed. The memory stack has been shown in below diagram.

Recursion VS Iteration

Now, let’s discuss a few practical problems which can be solved by using recursion and understand its basic working. For basic understanding please read the following articles.  Basic understanding of Recursion. Problem 1: Write a program and recurrence relation to find the Fibonacci series of n where n>2 .  Mathematical Equation:   

Recurrence Relation:  

Recursive program:  

Implementation:  

Time Complexity: O(2 n ) Auxiliary Space: O(n)

Here is the recursive tree for input 5 which shows a clear picture of how a big problem can be solved into smaller ones.  fib(n) is a Fibonacci function. The time complexity of the given program can depend on the function call. 

fib(n) -> level CBT (UB) -> 2^n-1 nodes -> 2^n function call -> 2^n*O(1) -> T(n) = O(2^n)  

For Best Case. 

Working:  

Problem 2: Write a program and recurrence relation to find the Factorial of n where n>2 .  Mathematical Equation:  

Recursive Program:   Input: n = 5  Output:   factorial of 5 is: 120 Implementation:  

Time complexity: O(n) Auxiliary Space: O(n)

Working:    

Diagram of factorial Recursion function for user input 5.

Example:  Real Applications of Recursion in real problems

Recursion is a powerful technique that has many applications in computer science and programming. Here are some of the common applications of recursion:

• Tree and graph traversal : Recursion is frequently used for traversing and searching data structures such as trees and graphs. Recursive algorithms can be used to explore all the nodes or vertices of a tree or graph in a systematic way.
• Sorting algorithms : Recursive algorithms are also used in sorting algorithms such as quicksort and merge sort. These algorithms use recursion to divide the data into smaller subarrays or sublists, sort them, and then merge them back together.
• Divide-and-conquer algorithms : Many algorithms that use a divide-and-conquer approach, such as the binary search algorithm, use recursion to break down the problem into smaller subproblems.
• Fractal generation : Fractal shapes and patterns can be generated using recursive algorithms. For example, the Mandelbrot set is generated by repeatedly applying a recursive formula to complex numbers.
• Backtracking algorithms : Backtracking algorithms are used to solve problems that involve making a sequence of decisions, where each decision depends on the previous ones. These algorithms can be implemented using recursion to explore all possible paths and backtrack when a solution is not found.
• Memoization : Memoization is a technique that involves storing the results of expensive function calls and returning the cached result when the same inputs occur again. Memoization can be implemented using recursive functions to compute and cache the results of subproblems.

These are just a few examples of the many applications of recursion in computer science and programming. Recursion is a versatile and powerful tool that can be used to solve many different types of problems.

Explanation: one real example of recursion:

Recursion is a programming technique that involves a function calling itself. It can be a powerful tool for solving complex problems, but it also requires careful implementation to avoid infinite loops and stack overflows. 

Here’s an example of implementing recursion in Python:

In this example, we define a function called factorial that takes an integer n as input. The function uses recursion to compute the factorial of n (i.e., the product of all positive integers up to n).

The factorial function first checks if n is 0 or 1, which are the base cases. If n is 0 or 1, the function returns 1, since 0! and 1! are both 1.

If n is greater than 1, the function enters the recursive case. It calls itself with n-1 as the argument and multiplies the result by n. This computes n! by recursively computing (n-1)!.

It’s important to note that recursion can be inefficient and lead to stack overflows if not used carefully. Each function call adds a new frame to the call stack, which can cause the stack to grow too large if the recursion is too deep. In addition, recursion can make the code more difficult to understand and debug, since it requires thinking about multiple levels of function calls.

However, recursion can also be a powerful tool for solving complex problems, particularly those that involve breaking a problem down into smaller subproblems. When used correctly, recursion can make the code more elegant and easier to read.

What are the disadvantages of recursive programming over iterative programming?   Note that both recursive and iterative programs have the same problem-solving powers, i.e., every recursive program can be written iteratively and vice versa is also true. The recursive program has greater space requirements than the iterative program as all functions will remain in the stack until the base case is reached. It also has greater time requirements because of function calls and returns overhead.

Moreover, due to the smaller length of code, the codes are difficult to understand and hence extra care has to be practiced while writing the code. The computer may run out of memory if the recursive calls are not properly checked.

What are the advantages of recursive programming over iterative programming?   Recursion provides a clean and simple way to write code. Some problems are inherently recursive like tree traversals, Tower of Hanoi , etc. For such problems, it is preferred to write recursive code. We can write such codes also iteratively with the help of a stack data structure. For example refer Inorder Tree Traversal without Recursion , Iterative Tower of Hanoi .

Summary of Recursion:

• There are two types of cases in recursion i.e. recursive case and a base case.
• The base case is used to terminate the recursive function when the case turns out to be true.
• Each recursive call makes a new copy of that method in the stack memory.
• Infinite recursion may lead to running out of stack memory.
• Examples of Recursive algorithms: Merge Sort, Quick Sort, Tower of Hanoi, Fibonacci Series, Factorial Problem, etc.

Output based practice problems for beginners:   Practice Questions for Recursion | Set 1   Practice Questions for Recursion | Set 2   Practice Questions for Recursion | Set 3   Practice Questions for Recursion | Set 4   Practice Questions for Recursion | Set 5   Practice Questions for Recursion | Set 6   Practice Questions for Recursion | Set 7 Quiz on Recursion   Coding Practice on Recursion:   All Articles on Recursion   Recursive Practice Problems with Solutions

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Advanced AI Configurations AI in Healthcare AI Tool Integration AI Training and Inference Edge Computing with AI Fine-Tuning Models Foundational Models Large Language Models LLM Configuration Local LLM Frameworks Text Generation Web UI Tutorial

Exploring Oobabooga Text Generation Web UI: Installation, Features, and Fine-Tuning Llama Model with LoRA

by Aditya Sharma on July 1, 2024

Table of Contents

Introduction

• What’s in Store for You?
• Overview of Oobabooga Text Generation Web UI

Interface Overview

User interaction, model response, action buttons, why is oobabooga text generation web ui important in our local llm series, setting up oobabooga text generation web ui, system requirements, operating systems, installation steps, automatic installation, manual installation.

• Docker-Based Installation:

Watch the Magic: Oobabooga Installation and Setup Walkthrough

Key points to note, features of oobabooga text generation web ui, user interface overview, default tab, parameters tab, generation sub-tab, training tab, overview of training tab, session tab, detailed overview of the model tab in oobabooga text generation web ui, key features, expanded model loader, transformers, llamacpp_hf, exllamav2_hf and exllamav2, autogptq and gptq-for-llama, other loaders, summary of the expanded model loader, instruction fine-tuning llama model with lora on a100 gpu using oobabooga text generation web ui interface, summary: key takeaways from the oobabooga text generation web ui tutorial, getting started with oobabooga text generation web ui, fine-tuning aspect, citation information.

In this tutorial, you will learn about Oobabooga Text Generation Web UI, a Gradio-based large language model (LLM) application that runs in a browser. This blog post is a comprehensive guide covering the essential aspects of setting up the web user interface (UI), exploring its features, and demonstrating how to fine-tune the Llama model in a parameter-efficient way using Low-Rank Adaptation (LoRA) directly within the application. As part of our ongoing local LLM series, this tutorial aims to showcase the versatility and power of running and fine-tuning LLMs on local setups.

This lesson is the last of a 4-part series on Local LLMs :

• Harnessing Power at the Edge: An Introduction to Local Large Language Models
• Inside Look: Exploring Ollama for On-Device AI

Integrating Local LLM Frameworks: A Deep Dive into LM Studio and AnythingLLM

• Exploring Oobabooga Text Generation Web UI: Installation, Features, and Fine-Tuning Llama Model with LoRA (this tutorial)

To learn about the Oobabooga Text Generation Web UI and how to fine-tune the LLaMA model efficiently using LoRA from within the application, just keep reading .

Welcome to the fourth installment of our comprehensive series on local large language models (LLMs). Today’s tutorial focuses on Oobabooga Text Generation Web UI, a Gradio-based application designed for LLMs. While this lesson is tailored more for developers, non-developers are also welcome to follow along. This tutorial will be a bit more technical as we delve into advanced features and fine-tuning capabilities.

The Oobabooga Text Generation Web UI is an important addition to our series because it not only allows for seamless text generation but also supports fine-tuning, making it a comprehensive tool for leveraging local LLMs.

If you have been following along with our series, you would have covered a wide array of different local LLM frameworks. In our first tutorial, Harnessing Power at the Edge: An Introduction to Local Large Language Models , we provided a foundational overview of local LLMs, discussing various model formats, quantization techniques, and a high-level overview of numerous local LLM frameworks.

From there, we dove deeper into Ollama in our second post, Inside Look: Exploring Ollama for On-Device AI . This tutorial garnered significant organic engagement and was appreciated by the Ollama team for its detailed exploration of Ollama’s installation, model registry, command-line interface (CLI) usage, and integration capabilities.

In our third lesson, Integrating Local LLM Frameworks: A Deep Dive into LM Studio and AnythingLLM , we explored two unique and powerful local LLM offerings: LM Studio and AnythingLLM. These tools stand out for their advanced features (e.g., AI agents, retrieval-augmented generation capabilities, and excellent user experience).

What’s in Store for You?

In this tutorial, we will focus on Oobabooga Text Generation Web UI, a unique Gradio-based application designed for text generation tasks. This tool stands out in our local LLM series for its capability to run directly in a browser and its versatility in both text generation and fine-tuning the LLaMA model using LoRA.

Overview of Oobabooga Text Generation Web UI: We’ll start by explaining what Oobabooga Text Generation Web UI is and why it’s an important addition to our local LLM series. We’ll then discuss its capabilities, the types of models it supports, and how it fits into the broader landscape of LLM applications.

Setting Up Oobabooga Text Generation Web UI: This section will guide you through the installation process, covering system requirements and step-by-step instructions for setting up the web UI on various platforms. We’ll also discuss the initial configuration and how to get the application running on local machines.

Features of Oobabooga Text Generation Web UI: Here, we’ll delve into the key features of Oobabooga Text Generation Web UI (e.g., its user interface, supported models, and unique functionalities). We’ll highlight how these features make it a powerful tool for text generation tasks.

Fine-Tuning Llama Models with LoRA: One of the standout capabilities of Oobabooga Text Generation Web UI is the ability to fine-tune LLMs using LoRA adapters. We’ll show you how to fine-tune a Llama model on a medical dataset, detailing the steps involved in preparing the dataset, setting up the fine-tuning process, and evaluating the results.

By the end of this tutorial, you’ll have a comprehensive understanding of Oobabooga Text Generation Web UI, from installation and features to advanced configurations and fine-tuning capabilities. This guide will equip you with the knowledge and tools needed to leverage the full potential of this powerful local LLM framework. Whether you’re looking to generate text, fine-tune models, or optimize your AI setup, this tutorial will provide the insights you need to succeed. Let’s dive in and unlock the power of Oobabooga Text Generation Web UI together!

Overview of Oobabooga Text Generation WebUI

Oobabooga Text Generation Web UI is a Gradio based application that allows users to perform text generation tasks directly in a browser. It supports a variety of models and formats, making it a versatile tool for different text generation needs. One of its standout features is the ability to fine-tune LLMs using LoRA adapters. This functionality makes Oobabooga Text Generation Web UI a comprehensive tool for leveraging local LLMs. Its goal is to become the AUTOMATIC1111/stable-diffusion-webui of text generation.

It simplifies the deployment process and makes it easier to interact with models through a web browser without needing extensive web development skills. Unlike other local LLM frameworks we’ve explored (e.g., Ollama, LM Studio, and AnythingLLM), Oobabooga Text Generation Web UI does not have a standalone web application. Instead, being a Gradio-based application, it can run on your local host or leverage Gradio’s inherent properties to generate a public URL that is accessible for 72 hours. This means you can access and interact with the web UI via a browser, providing flexibility and convenience for various use cases.

The image below showcases the user interface of the Oobabooga Text Generation Web UI, highlighting the chat interface of this Gradio-based application designed for running large language models (LLMs) in a browser. The screenshot highlights an interaction where a user is asking the model to write a Python script that creates a temporary file, writes a random 16-character password to it, and prints its path. Here’s a detailed breakdown of the elements in the image:

Tabs at the Top: The interface includes several tabs (e.g., Chat , Default , Notebook , Parameters , Model , Training , and Session ) . The Chat tab is currently active, indicating that this section is for conversational interactions with the model.

User Input: At the top of the chat, the user has provided an input:

Initial Response: The model provides a Python script to fulfill the request:

The script generates a temporary file and writes a random 16-character password to it. However, the user points out that the tempfile module is not imported.

User Correction: The user responds:

Model Correction: The model acknowledges the oversight and provides a corrected version:

Buttons at the Bottom: The interface includes several action buttons:

• Stop : To stop the current operation.
• Impersonate : Likely to simulate another user’s input or action.
• Regenerate : To generate a new response based on the same input.
• Remove last : To remove the last interaction or response.

This interaction exemplifies how the Oobabooga Text Generation Web UI facilitates a conversational interface for generating and correcting code snippets interactively. The model is capable of understanding user feedback and making necessary adjustments to its responses, demonstrating an iterative process of refining code through user and model collaboration.

The primary reason we chose to cover Oobabooga Text Generation Web UI in our Local LLM series is its distinctiveness compared to other local LLM frameworks we’ve explored in previous lessons. It stands out in the broader Local LLM ecosystem, offering a superior developer experience, especially for those with intermediate knowledge of LLMs and the ongoing research in this field. Here’s why Oobabooga is a crucial addition to our series:

Developer-Centric Experience: Oobabooga Text Generation Web UI is tailored for developers who have a good grasp of LLM concepts and seek a more advanced tool for their projects. Unlike user-friendly applications (e.g., ChatGPT) or relatively technical ones (e.g., LM Studio), Oobabooga provides a sophisticated environment that necessitates a deeper understanding of LLMs.

Support for Multiple Model Backends: One of Oobabooga’s standout features is its support for multiple model backends. While frameworks like LM Studio and Ollama primarily support specific formats like GGUF (handled via Llama.cpp), Oobabooga goes beyond by supporting a variety of backends (e.g., Transformers, ExLlama v2, AutoGPTQ, AutoAWQ, and GPTQ-for-Llama). This versatility significantly broadens the range of models you can work with, making it a powerful tool for diverse AI applications.

Training and Fine-Tuning Capabilities: Oobabooga excels in its ability to train new LoRA adapters with custom data. Users can load and unload LoRA adapters on the fly, facilitating seamless text generation tasks. In this tutorial, we’ll demonstrate how to train a LoRA adapter for a Llama model on medical data. This will involve instruction fine-tuning using the Alpaca chat template, showcasing the ease and efficiency of the process. The ability to integrate and utilize fine-tuned models for specific domains is a game-changer for personalized AI applications.

Comprehensive Operating System Support: Like other local LLM frameworks, Oobabooga supports major operating systems, including macOS (with MPS for M1, M2, and M3 chips), Linux (CPU and NVIDIA), and Windows (CPU and NVIDIA). This cross-platform compatibility ensures that users can leverage the tool regardless of their hardware setup, though there may be some performance differences due to underlying library optimizations.

Gradio-Based Web Application: Unlike many local LLM frameworks that lack a web interface, Oobabooga Text Generation Web UI leverages Gradio to provide a browser-based application. This means it can run on your local host or use Gradio’s inherent properties to generate a public URL accessible for 72 hours, making it highly versatile for both local and remote access.

In conclusion, Oobabooga Text Generation Web UI offers a unique set of features and capabilities that set it apart in the local LLM landscape. Its advanced developer-centric tools, multi-backend support, and seamless fine-tuning options make it an invaluable addition to our series. In the following sections, let’s delve deeper into this powerful tool and explore its full potential.

In this section, we will look at the system requirements, including the minimum hardware and operating system configurations needed to set up Oobabooga. We will also guide you through the installation process using the provided one-click shell scripts.

Additionally, we have recorded a screen capture of the installation process on a NVIDIA A100 GPU machine, which will be shown to help you better understand the setup. So, let’s go through this section together.

Before installing the Oobabooga Text Generation Web UI, ensure your system meets the following requirements:

Linux, Windows, macOS, WSL

• GPU: NVIDIA, AMD, Apple Metal (M1, M2, and M3 chips), or CPU-only
• Memory: Minimum 8GB RAM (16GB recommended)
• Storage: At least 10GB of free disk space
• Python: Version 3.11
• Conda: Miniconda or Anaconda for managing dependencies

Follow these steps to install the Oobabooga Text Generation Web UI:

Clone or download the repository:

Run the installation script:

• Linux: start_linux.sh
• Windows: start_windows.bat
• macOS: start_macos.sh
• WSL: start_wsl.bat

Select your GPU vendor when prompted.

Access the web UI:

• Once the installation completes, navigate to http://localhost:7860/?__theme=dark
• Public Access: To access the application on a public URL, add the --share flag while running the start_linux.sh script. This will generate a public link that you can use to access the application remotely.

Restarting the web UI: To restart in the future, run the start_linux.sh script again.

For those who prefer manual installation, here are the general steps:

• Install Miniconda or Anaconda.
• Create and activate a Conda environment.
• If you have a Linux-based system with an NVIDIA GPU, install PyTorch with the appropriate CUDA version.
• If you have a Linux-based system with no GPU, install the CPU-only version of PyTorch.
• Ensure the PyTorch version matches the CUDA version compatible with your NVIDIA driver.
• For macOS with MPS (Apple M-series GPU), install the appropriate PyTorch version.
• Clone the repository.
• Navigate to the repository directory.
• Install the required packages from requirements.txt .
• Start the server manually and access the web UI.

Note: For more detailed instructions, refer to the Oobabooga repository’s README.md .

Docker-Based Installation

Oobabooga Text Generator Web UI also supports Docker-based installation. Although we won’t cover it in detail here, it’s worth mentioning that Docker installation is available for various configurations:

Installation is managed using Docker Compose, providing a robust and isolated environment for running the web UI.

In this section, you will see a quick walkthrough of how to install the Oobabooga Text Generation Web UI using the provided automatic installation shell script. This video, which is a screen capture, guides you through the entire installation process on a Linux machine with NVIDIA A100 GPU.

NVIDIA Driver and CUDA Compatibility:

• The video demonstrates the installation on an NVIDIA A100 GPU with the NVIDIA driver version 520. When running nvidia-smi , it shows the driver version, which is not compatible with CUDA 12.1 (the default in the script).
• Due to this incompatibility, the installation is performed using CUDA 11.8, which is supported by the NVIDIA driver version 520.

Installation Steps:

• Whether you have an NVIDIA GPU, or if you are installing on an Intel or Mac Metal GPU.
• Which CUDA version to use (11.8 or 12.1).
• The type of GPU (RTX/GTX series or older Kepler GPUs).
• For this setup, NVIDIA is selected, CUDA 11.8 is chosen, and the appropriate GPU type is specified.

Automatic Setup:

• After providing the necessary inputs, the script takes over and completes the installation automatically. No further user intervention is required.

Final Steps:

• In the last 15 seconds of the video, you can see the Gradio application up and running on port 7860 , which is the default port for Gradio applications hosted on localhost.

Enjoy the video, and we hope you find this walkthrough helpful!

In this section, we will explore the key features of Oobabooga Text Generation Web UI, delving into its user interface, supported models and formats, and various functionalities that make it a robust tool for text generation tasks. We’ll provide an overview of the user interface, examining different tabs and their purposes. Additionally, we’ll highlight the range of model loader frameworks it supports and discuss some of the unique tools and functionalities it offers.

Oobabooga Text Generation Web UI boasts a well-organized and user-friendly interface designed to enable smooth interactions with the models. The interface comprises several key tabs, which we will explore in detail. We’ve already taken a brief look at the chat interface in the overview section, and now we’ll delve into the rest.

The Default tab in the Oobabooga Text Generation Web UI serves as a powerful workspace for generating and refining text, distinct from the Chat tab. While the Chat tab is optimized for interactive, conversational exchanges with the model, the Default tab is geared more toward structured text generation tasks, allowing for more control and customization in the output.

It offers an Input field on the left where you can enter prompts and an Output field on the right that displays the generated text. The interface is designed to be intuitive and user-friendly, making it easy to navigate and utilize its features effectively.

Key Features of the Default Tab

Input Field: This is where users can type or paste their prompts. The Input field supports markdown, allowing for more structured and formatted text inputs.

Output Field: The generated text appears here. The Output field can display text in Raw , Markdown , or HTML formats, providing flexibility in how the content is viewed and utilized.

Action Buttons: Below the Input and Output fields, there are several action buttons:

• Generate : Initiates the text generation process based on the input prompt.
• Stop : Halts the generation process if needed.
• Continue : Allows the generation process to proceed further, extending the current output.
• Count tokens : Provides a token count for the input prompt, which is useful for understanding the complexity and length of the input.

Prompt Dropdown: Users can select different types of prompts from a dropdown menu to tailor the output according to their needs. One of the predefined prompt types is the “alpaca with input” prompt type, which can be used to fine-tune the generated text for specific use cases or formats.

The Default tab is a versatile tool for generating text, offering a streamlined interface that caters to both basic and advanced users. Whether you’re crafting detailed articles, conducting research, or engaging in dynamic conversations with the model, this tab provides a robust environment for your text generation needs. It allows for greater flexibility and customization compared to the Chat tab, making it ideal for more specific and complex text generation tasks.

The Parameters tab in the Oobabooga Text Generation Web UI is a comprehensive section that allows users to fine-tune and control the behavior of the model during text generation. This tab is essential for users who want to customize the output to meet specific requirements and optimize the model’s performance.

The Parameters tab is divided into several sub-tabs, each focusing on different aspects of the model’s functionality. The primary sub-tabs include Generation , Character , Instruction template , Chat history , and Upload character .

The Generation sub-tab is where users can adjust the various parameters that influence the text generation process. Here are some of the key parameters available:

• max_new_tokens : Sets the maximum number of new tokens to generate in the output. This controls the length of the generated text.
• temperature : Adjusts the randomness of the model’s predictions. Higher values (e.g., 1.0 ) produce more random outputs, while lower values (e.g., 0.2 ) produce more deterministic outputs.
• top_p : Controls nucleus sampling, a technique that selects tokens from the top p probability mass. Setting it to 0.9 means the model will consider only the top 90% probable tokens for generation.
• top_k : Limits the number of highest probability tokens considered for generation. For example, setting it to 20 means only the top 20 tokens are considered at each step.
• repetition_penalty : Applies a penalty to repeated sequences of tokens, encouraging the model to generate more diverse text.
• guidance_scale : Used for CFG (Classifier-Free Guidance), which helps in guiding the text generation process.
• num_beams : Sets the number of beams for beam search, a method for exploring multiple potential outputs and selecting the best one.
• length_penalty : Adjusts the penalty for the length of the generated sequence. Higher values favor shorter sequences, while lower values allow longer sequences.

Additionally, users can turn on or off various options, such as:

• do_sample : Turns on or off sampling of tokens.
• truncate : Limits the prompt length by removing tokens from the beginning if it exceeds the specified length.
• early_stopping : Stops the generation once the model has determined a likely end of the sequence.
• Skip special tokens : Instructs the model to skip special tokens in the output.
• Activate text streaming : Allows the output to be streamed as it is generated, providing real-time feedback.

The Generation sub-tab offers an extensive range of parameters, giving users precise control over the text generation process. This level of customization is particularly useful for developers and advanced users who need to tailor the model’s output to specific use cases.

The Parameters tab is a powerful tool in the Oobabooga Text Generation Web UI, providing users with the flexibility to optimize and refine the text generation process to suit their needs.

The Training tab in the Oobabooga Text Generation Web UI is a critical feature that allows users to fine-tune models, specifically using the LoRA (Low-Rank Adaptation) method. This tab provides various parameters and options for setting up and controlling the training process. Here’s a detailed overview of the Training Tab and its functionalities:

The Training tab is divided into several sections, each focusing on different aspects of the training process. This structured layout ensures that users can easily navigate and configure the settings required for effective model fine-tuning.

• Copy parameters from : Allows users to copy parameters from an existing setup to streamline the training configuration process.
• Name : Users can specify the name of the new LoRA file. If the name is the same as an existing file, checking the “ Override Existing Files ” option will replace the old file.

Target Modules

• LoRA Rank : Also called the dimension count. Higher values mean a larger file and more content control, while smaller values mean a smaller file and less control.
• LoRA Alpha : Scaling factor of the LoRA. A good standard value is twice the rank.
• Batch Size : The global batch size determines gradient accumulation, affecting the quality of training.
• Micro Batch Size : Per-device batch size. Increasing this value will use more VRAM.
• Cutoff Length : Sets the cutoff length for input text, ensuring it doesn’t exceed a certain limit.
• Save every n steps : Allows setting checkpoints to save the progress of every specified number of steps.
• Epochs : Number of times every entry in the dataset should be fed into training.
• Learning Rate : Defines the rate at which the model learns. A good starting point is 3e-4 (0.0003).
• LR Scheduler : Defines how the learning rate changes over time. Options include constant , linear , cosine , etc.

Dataset Configuration

• Formatted Dataset : Specifies the format of the dataset used for training.
• Raw text file : Provides the option to use raw text files for training.
• Dataset : Specifies the dataset file to use for training.
• Evaluation Dataset : An optional dataset used to evaluate the model after training.
• Evaluate every n steps : Tests the model for every specified number of steps using the evaluation dataset.

Training Control

• Start LoRA Training : Initiates the training process with the configured parameters.
• Interrupt : Stops the training process if needed.

The Training tab offers extensive customization options, allowing users to fine-tune their models according to specific requirements. This level of control is particularly beneficial for developers and advanced users aiming to optimize their models for particular tasks or datasets.

By utilizing the parameters and settings available in the Training tab, users can achieve efficient and effective model fine-tuning, enhancing the overall performance and applicability of their LLMs.

The Session tab in the Oobabooga Text Generation Web UI provides users with extensive control over the application’s extensions and command-line flags. This tab is essential for customizing the Web UI’s behavior and adding new functionalities through extensions. Here, you can restart the UI with new settings.

Here are the main features of the Session tab:

Available Extensions

The left panel lists all available extensions that can be enabled to enhance the Web UI’s capabilities. Some extensions may require additional Python dependencies, which can be installed using the provided command ( pip install -r extensions/extension_name/requirements.txt ).

Examples of available extensions include:

• character_bias
• google_translate
• send_pictures
• whisper_stt
• And many more.

Boolean Command-Line Flags

The middle panel allows users to toggle various command-line flags that modify the Web UI’s behavior. These flags include:

• api : Enables API access.
• auto_launch : Automatically launches the Web UI upon startup.
• chat_buttons : Adds chat-specific buttons to the interface.
• deepspeed : Enables DeepSpeed optimization.
• force_safetensors : Forces the use of SafeTensors format.
• multi_user : Supports multiple users.
• nowebui : Disables the Web UI.
• public_api : Makes the API publicly accessible.
• share : Generates a shareable Gradio public link for the session.
• verbose : Enables verbose logging for debugging purposes.

Extension Management: The right panel allows users to install or update extensions by entering the GitHub URL of the desired extension. This feature provides flexibility to add new functionalities as needed.

Apply Flags/Extensions and Restart: After selecting the desired extensions and flags, users can apply the changes and restart the Web UI to activate the new settings. This ensures that any modifications take effect immediately.

Save UI Defaults to settings.yaml: Users can save the current configuration as defaults in the settings.yaml file. This is useful for maintaining a consistent setup across different sessions.

Toggle: The toggle button allows users to switch between different sets of extensions and flags easily.

The Session tab in the Oobabooga Text Generation Web UI is a powerful tool for users looking to customize their text generation environment. By leveraging the available extensions and command-line flags, users can tailor the Web UI to meet their specific needs, whether for development, research, or production purposes.

The Model tab in the Oobabooga Text Generation Web UI is essential for managing and fine-tuning pre-trained models. This section explains how to load models, apply LoRAs, and download new models, providing comprehensive configuration options tailored to various model formats and quantization techniques.

Downloading Models

• On the right side of the Model tab, you can input the Hugging Face model path (e.g., facebook/galactica-125m ) to download models directly to your system. You can specify branches and download specific files within the model repository.

Loading Models

• After downloading, models appear in the dropdown menu on the left. You can select a model and load it by clicking the “ Load ” button.
• The “ Autoload the model ” checkbox automatically loads the selected model without the need to click “ Load ” manually.
• Options are available to Unload , Reload , and Save settings for the current model, providing flexibility in managing model states.

Configuration Options

• Depending on the selected model loader, various configuration options are provided. These include CPU memory allocation, 4-bit loading parameters, and other loading options.
• As shown in the image, when the model loader is set to “ Transformers ,” you can configure options such as compute data type ( compute_dtype ), quantization type ( quant_type ), alpha value ( alpha_value ), rope frequency base ( rope_freq_base ), and more.
• Changing the model loader to alternatives like llama.cpp , AutoGPTQ , or AutoAWQ will result in different configuration options, which will be discussed in the following “Expanded Model Loader” section.

The model loader selection impacts the available configuration options, as different loaders are tailored for various model formats and quantization techniques. Here’s an in-depth look at each model loader option:

Please note that the configurations provided are detailed and highly specific. While we have yet to experiment with all these settings personally, this overview should give you an insight into the extensive capabilities of the Oobabooga Text Generation Web UI. This platform includes a wide range of parameters to optimize model performance and accuracy. We recommend further exploration of these configurations online or focusing on a particular model loader like llama.cpp to fully understand its various settings and their interactions.

Purpose: General loader for transformer-based models, typically in full precision (16-bit or 32-bit). Often used for models like those in Hugging Face repositories.

Configuration:

• gpu-memory : Sets GPU memory limit for CPU offloading.
• cpu-memory : Sets CPU memory limit, with overflow going to disk.
• compute_dtype, quant_type : Set when using 4-bit loading.
• alpha_value , rope_freq_base , compress_pos_emb : Various settings for extending context length and optimizing embeddings.
• Additional Options: Includes settings for 8-bit loading, bf16 precision, auto device allocation, disk offloading, and more.
• Example: Vicuna-7B-v1.5 .

Purpose: Specifically for models in GGUF format.

• n-gpu-layers : Number of layers to allocate to the GPU.
• n_ctx : Context length of the model, with higher values requiring more VRAM.
• tensor_split : Memory allocation per GPU in multi-GPU setups.
• Additional Options: Includes batch size, number of threads, tensor core support, streaming LLM, and CPU-only mode.
• Example: Llama-2-7b-Chat-GGUF .

Purpose: Similar to the llama.cpp but integrates with transformers’ samplers and tokenizers.

Configuration: Nearly identical to llama.cpp with additional support for transformers’ tokenizer. Includes an option ( logits_all ) for perplexity evaluation.

Purpose: For models quantized using ExLlama v2, optimizing for efficient inference on limited hardware.

• gpu-split : Memory allocation per GPU in multi-GPU setups.
• max_seq_len : Maximum sequence length for pre-allocated cache.
• cfg-cache , no_flash_attn , cache_8bit , cache_4bit : Various settings for cache configuration and disabling flash attention.
• Example: Llama2-70B-exl2 .

Purpose: Loaders for models quantized using General Purpose Quantization (GPTQ).

• wbits , groupsize , triton : Parameters for setting model precision and group size.
• no_inject_fused_attention , no_inject_fused_mlp , no_use_cuda_fp16 , desc_act : Various performance and compatibility settings.
• Example: Llama-2-13B-chat-GPTQ .

Purpose: For models quantized using AWQ technique.

Configuration: Similar to AutoGPTQ but tailored for AWQ optimization.

Example: Phind-CodeLlama-34B-v2-AWQ .

QuIP and HQQ : Specialized loaders for specific model formats and quantization techniques optimized for certain tasks and hardware setups.

The Model tab in the Oobabooga Text Generation Web UI offers a comprehensive interface for downloading, configuring, and optimizing pre-trained models. It supports various model formats and quantization techniques, ensuring efficient management and utilization of models for diverse tasks. This flexibility makes it invaluable for both research and production environments.

For more detailed information, you can refer to the Oobabooga Text Generation Web UI documentation .

To understand how to perform instruction fine-tuning with the Llama Model using the LoRA Adapter and the Alpaca’s Chat Template on a Medical Dataset, please refer to the tutorial video at the top of this blog post. In this video, we cover the entire process, including:

• An overview of LoRA-based fine-tuning.
• How to prepare the Medical Data Ground Truth, including the conversion and preparation of input-output data in the Alpaca Chat Template format for the Llama Model.
• Feeding the prepared data along with the pre-trained Llama Model into the Oobabooga Text Generation Web UI to fine-tune the model on the Medical Dataset.
• An evaluation where we chat with the pre-trained Llama Model and compare its responses to those of the LoRA fine-tuned adapter.

To watch the full process in detail, please view the tutorial video included in this blog post. This video will provide you with step-by-step instructions and insights into fine-tuning the Llama model effectively.

What's next? We recommend PyImageSearch University .

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As we wrap up this tutorial, let’s revisit the primary objectives.

This section provided a detailed overview of the installation process for the Oobabooga Text Generation Web UI, covering system requirements and offering step-by-step guides for automatic, manual, and Docker-based installations. We also explored the importance of Oobabooga in the context of our local LLM series, highlighting its role in enhancing text generation capabilities.

We delved into the various features of the Oobabooga interface, showcasing its robust capabilities and user-friendly design.

This subsection provided an in-depth look at the Oobabooga user interface, breaking down the functionalities of each tab. The Default tab’s simplicity, the Parameter tab’s customization options, the Generation sub-tab’s flexibility, the Training tab’s comprehensive settings, and the Session tab’s management capabilities were all highlighted to illustrate the robustness of the UI.

We explored the key features of the Model tab, including the expanded model loader and its summary features. This section emphasized the ease with which users can load and manage different models, enhancing the overall user experience.

While our blog post does not cover the instruction fine-tuning of the Llama model with LoRA in the Oobabooga Text Generation Web UI, our video covers this topic extensively. We highly recommend checking out the video, where we also demonstrate how to load a pre-trained Llama model in GGUF format and other quantized model formats like AWQ or GPTQ for chat.

This comprehensive guide not only improves productivity but also showcases Oobabooga’s versatility as a powerful tool for text generation. By leveraging its robust features and intuitive interface, users are well-equipped to harness the full potential of local LLM frameworks for advanced AI applications.

Sharma, A. “Exploring Oobabooga Text Generation Web UI: Installation, Features, and Fine-Tuning Llama Model with LoRA,” PyImageSearch , P. Chugh, A. R. Gosthipaty, S. Huot, K. Kidriavsteva, and R. Raha, eds., 2024, https://pyimg.co/qtg28

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About the Author

Aditya Sharma is a Computer Vision and Natural Language Processing research engineer working at Robert Bosch. In addition, he is an experienced technical writer with over 50 published reports. Aditya has been fortunate to have associated and worked with premier research institutes of India such as IIT Mandi and CVIT Lab at IIIT Hyderabad.

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