Video demonstrates the fine-tuning of the GPT2 model for custom natural language generation tasks. Steps covered for training the GPT2 model:
1. Data Preparation for our own use-case.
2. Model Download.
3.Fine-Tune the Model settings.
4.Train the model.
5.Evaluate the Performance using Tensorboard.
6.Generate the Next Sentence for a given piece of Sentence from our trained vocabulary.

Links:
SimpleTransformer: https://simpletransformers.ai/docs/lm-specifics/
Notebook Link: https://github.com/karndeepsin....gh/Custom-Next-Sente

Train Custom NER model using Bert: https://www.youtube.com/watch?v=uKPBkendlxw&t=16s

Train Custom Text Classification using BERT: https://www.youtube.com/watch?v=irU1q0kXekE

Text Annotation For NLP tasks: https://www.youtube.com/watch?v=vT-GE_jssPk&t=1s


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Connect with me on:
LinkedIn: https://www.linkedin.com/in/karndeepsingh
Github: https://www.github.com/karndeepsingh

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PROMPT SHOWN IN VIDEO:
"When it comes to writing content, two factors are crucial, "perplexity" and "burstiness." Perplexity measures the complexity of text. Separately, burstiness compares the variations of sentences. Humans tend to write with greater burstiness, for example, with some longer or complex sentences alongside shorter ones. AI sentences tend to be more uniform. Therefore, when writing the following content I am going to ask you to create, I need it to have a good amount of perplexity and burstiness. Do you understand?"


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#chatgpt
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In this tutorial, learn how to use specific prompts to get AI tools like ChatGPT to generate 100% human-like content. Discover the secrets to creating natural language and fooling even the most advanced AI algorithms. Get ready to take your chatbot game to the next level! Watch now.

Affiliate disclaimer:
Keep in mind that we may receive commissions when you click our links and make purchases. However, this does not impact my reviews and product how-tos.

In today's video I discuss the difference between chatgpt and gpt -3
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We also discuss:
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what are the use cases for chapt gpt
what are the use cases for gpt 3
how is chatgpt different that gpt 3
Why chatgpt is much more powerful and intriguing compared to gpt 3.5
how you can use chatgpt
the limitations of gpt 3
which is better?

Disclaimer: This video and description may contain affiliate links, which means that if you click on one of the product links, I’ll receive a small commission. This helps support the channel and allows us to continue to make videos like this. Thank you for the support!

Ready to start fine-tuning your AI model? Not without this big boy!

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Looking to level up your content game? Look no further than Chat GPT and Playground! In this video, we'll show you exactly how to use these powerful tools to create content that stands out from the crowd.

Whether you're a blogger, marketer, or content creator, Chat GPT and Playground can help you take your content to the next level. With their intuitive interfaces and powerful features, you'll be able to craft engaging and informative content that your audience will love.

So why wait? Watch this video now to learn how to use Chat GPT and Playground to level up your content and take your online presence to the next level!

Affiliate disclaimer:
Keep in mind that we may receive commissions when you click our links and make purchases. However, this does not impact my reviews and product how-tos.

Hello everyone, In this video, you will learn how to use GPT-3 for the Question Answering System using Gradio in Python. Moreover, this video also how you can perform smart prompting on OpenAI Playground. Hopefully, you will like it.

Do not forget to subscribe to our channel.

Watch our Python Basic Tutorials:

🚴🏽 Python Complete Course: https://youtube.com/playlist?list=PLQ...
🚴🏽 Machine Learning: https://youtube.com/playlist?list=PLQ...

For more details about Python and MLOPs follow me:
⚡️ LinkedIn: https://www.linkedin.com/in/zaibhamid/
⚡️ Github: https://github.com/A-I-Studio/GPT-3-Projects
⚡️ Website: https://developwithai.com/

Read my local PDF files and summarize content with 1-click in GPT systems like: GPT-4, BING Chat, ChatGPT, ...

Subscribers ask, free solutions delivered immediately.

Note: Please do not share personal or sensitive information with LLMs, since theoretically (worst case) your data become public data.


#ai
#gpt4
#chatgpttutorial
#pdf
#summarized

We'll answer the questions:
What's the difference?
Do I need to choose one over the other?
How can I use both to keep costs down and maintain control?

This course will teach you how to build AI-powered apps with the ChatGPT, Dall-E and GPT-4 APIs. Go here to try the interactive browser-version: https://scrimba.com/learn/buildaiapps

✏️ This course was created by Tom Chant, a teacher at Scrimba. If you have any feedback to Tom, please reach out to him on Twitter here:
https://twitter.com/tpchant

Also, follow Scrimba on YouTube here: https://www.youtube.com/c/Scrimba

We recommend that you learn basic HTML, CSS, and JavaScript before taking this course. Here are two free courses that will get you up to speed:
🔗 HTML & CSS: https://scrimba.com/learn/htmlandcss
🔗 JavaScript: https://scrimba.com/learn/learnjavascript

⭐️ Code ⭐️
🔗 Download via Scrimba: https://scrimba.com/learn/buildaiapps

💫 Links mentioned in course:
🔗 GPT-4 waiting list: https://scrimba.com/links/gpt4-waitlist-openai
🔗 OpenAI Home: https://scrimba.com/links/openai
🔗 OpenAI Docs: https://scrimba.com/links/openai-docs-intro
🔗 OpenAI Completions endpoint docs: https://scrimba.com/links/openai-completions-docs
🔗 GPTTools.com model comparison: https://scrimba.com/links/open-ai-comparison-tool
🔗 OpenAI Playground: https://scrimba.com/links/open-ai-playground
🔗 Dall-E: https://scrimba.com/links/dall-e-openai
🔗 OpenAI endpoint compatibility table: https://scrimba.com/links/chat....gpt-endpoint-compati
🔗 GPT-4 Chatbot conversation object format: https://scrimba.com/links/chatgpt-object-format
🔗 Data used to fine-tune We-Wingit Chatbot: https://scrimba.com/links/we-wingit-data-csv
🔗 Firebase home: https://scrimba.com/links/firebase-home
🔗 Firebase .val() method: https://scrimba.com/links/firebase-val-method
🔗 Object.values MDN: https://scrimba.com/links/object-dot-values
🔗 Netlify: https://scrimba.com/links/netlify-home

⭐️ Contents ⭐️
0:00:00 Introduction
0:01:19 Course Intro
0:04:56 MoviePitch intro
0:07:53 The Boilerplate
0:11:26 Getting an OpenAI API Key
0:13:32 Getting info for fetch request
0:15:14 Building an OpenAI fetch request
0:20:23 The first AI fetch request
0:26:41 Models
0:30:18 Tools
0:34:03 Refactor to use dependency l - env variable
0:38:11 Refactor to use dependency ll - The dependency
0:41:07 Refactor to use dependency lll - update fetchReply
0:44:40 Take out of Scrimba
0:46:45 Personalising the message
0:53:04 Tokens
0:57:09 fetchSynopsis
1:03:44 Aside - few shot approach
1:10:45 Aside - few shot approach ll
1:13:42 Refactor fetchSynopsis
1:21:00 Architecture
1:23:23 Title and Temperature
1:31:52 Reaching for the stars
1:37:52 Aside - createImage
1:46:56 fetchImagePrompt
1:54:21 Displaying the image and finishing off the UX
2:03:16 OutroKnowItAll: GPT-4 Chatbox2:06:47 KnowItAll Intro
2:09:40 Starter Code
2:13:10 Aside: How ChatGPT models work for chatbots
2:18:24 Conversation and instructions
2:20:21 Add user input to conversation array
2:23:06 The createChatCompletion endpoint
2:24:38 The model and object
2:28:46 Render the output, update the array
2:33:37 Aside: Theory: Frequency and presence penalties
2:37:07 presence_penalty practice
2:38:36 frequency_penalty practice
2:44:54 The chatbot’s personality
2:47:06 Firebase Intro
2:48:27 Firebase Account and database set up
2:50:43 Firebase dependency and database set up
2:55:53 Push method and instructions object
2:58:33 Update fetch Reply
3:02:24 Update fetchReply 2
3:04:49 Update the database
3:07:19 Render the conversation from the DB
3:12:02 The “start over” button
3:15:20 OutroWe-Wingit: Fine-tuned chatbot3:17:28 Intro to fine-tuning
3:20:04 Convert the Chatbot to We-Wingit
3:22:15 An Overview of the AI
3:23:52 Data for fine-tuning
3:26:34 The data we’re using
3:30:05 CLI 1 - Setting up the environment
3:33:03 CLI 2 - Data Preparation Tool
3:37:03 CLI 3 - Tuning the model
3:38:55 Updating the JS 1
3:41:33 Updating the JS 2
3:44:15 Updating the JS 3
3:47:01 The Separator
3:52:32 Aside - Stop Sequence
3:55:50 Adding the stop sequence
4:00:36 n_epochs
4:07:24 Intro to deployment
4:09:46 Download and GitHub
4:12:07 Netlify sign-up
4:13:56 Add Netlify env var
4:15:54 Netlify CLI
4:17:30 Netlify serverless function 1
4:19:52 Update fetchReply
4:24:28 Serverless function 2
4:27:30 Serverless function 3
4:29:21 Serverless function 4
4:32:32 Outro

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--

Learn to code for free and get a developer job: https://www.freecodecamp.org

Read hundreds of articles on programming: https://freecodecamp.org/news

My E-Book with 400+ Chat GPT Prompt Examples: https://bit.ly/ChatGPT_400_UseCases

Become an affiliate for my e-book and make 50 % off every sale: https://theaiadvantage.kartra.....com/affiliates/40233

I'm going to share some of the 400 amazing Chat GPT prompts that I collected. I'm sure you'll find them extremely useful to help you with productivity, learning new skills, getting creative with copywriting, and even finding funny nicknames for your pet. I'll take you through some of my favorite prompts from the five categories, and you'll be surprised at how easy it is to generate ideas and get advice from seasoned professionals. So let's dive right in and learn how to use Chat GPT!

For more free content on Chat GPT Prompts check out my channel and my weekly newsletter.

Links:
Chat GPT: https://chat.openai.com/
---------------------------------------------------------------------------------

Prompts:
🤔 Can you find some practical ways to practice/develop [skill] without joining a course or a community?
🤨 In [society/culture] is it generally considered to be [characteristic] or [characteristic]?
🥗 Can you create a [number]-day meal/diet plan for [age group] who needs to consume [number] calories per day but make it [restrction]-friendly?
🐶 Can you come up with a funny nickname for a [subject] that incorporates a play on words?

Chapters:
0:00 My collection of 400+ prompts
0:53 Learn fast
2:26 Social category
3:32 Improve your health with AI
4:55 Funny names for your pet

#chatgpt #chatgptprompts #prompts

---------------------------------------------------------------------------------

🧠 ChatGPT Prompt Engineering Course: https://aiadvantagecourse.com
🤯 E-Book with 750+ ChatGPT Use Cases: https://chatgpt.myaiadvantage.com
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How do language models like chatGPT and Palm work? A short cartoon that explains transformers and the tech behind LLMs.
Part 2: https://youtu.be/YDiSFS-yHwk

0:05 - autocomplete
0:44 - search query completion
1:03 - language modeling with probabilities
1:59 - time series and graphs
2:34 - text generation
3:43 - conditional probabilities
3:52 - trigrams
4:49 - universal function approximation
5:19 - neural networks
6:33 - gradient descent
7:03 - back propagation
7:24 - network capacity

ChatGPT is more than just a language model, it can be used to create websites, businesses and much more. And I would know best, as I created, built, and sold a business using OpenAI platform just this year. So in this video, I’m going to explain how to use ChatGPT and its models so you can do the same. The video is structured in three parts.

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This is new and ready for those looking to kickstart their own app or website using the OpenAI GPT models. I've built it on MERN it should save you over 100 hours if you want to build or test your own ideas! This also supports the channel if you have found these videos of benefit!

New - ChatGPT Starter Kit
https://enhanceui.gumroad.com/....l/chatgpt-template-s

Video 1 - What is ChatGPT (Introduction)
https://youtu.be/40Kp_fa8vIw

Video 2 - Crash Course ChatGPT
https://youtu.be/JTxsNm9IdYU

Video 3 - I created a SaaS in 30 days
https://youtu.be/UBG_YiTg_Bs

OpenAI ChatGPT:
https://chat.openai.com/chat

#chatgpt #website #ai

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A book I've created to help you improve the look of your apps and websites.
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Thank God! I don't have to remember formulas. Connect ChatGPT API using GPT 3.5 Turbo model by OpenAI inside Google Sheets. Ask direct questions to Chat GPT through ChatGPT API inside Google Sheets using GPT 3.5 Turbo Model which is the latest GPT model by OpenAI.

CODE: https://docs.google.com/docume....nt/d/15N6C0-2bpU8FvQ

VIDEOS you might LIKE:

Create AskGPT App: Use GPT 3.5 Turbo Model (ChatGPT API)
https://youtu.be/Pve6tJiqNc4

AI that converts GPT-3 to Video directly
https://youtu.be/q41s2CpK17s

Build AI Writer on ANY TOPIC and in ANY LANGUAGE (OpenAI + GoogleDocs)
https://www.youtube.com/watch?v=7YGIjivdP2c&t=26s

Google Sheets + OpenAI GPT3: Integrate and Use GPT3
https://youtu.be/sZglG2rJXL4

AI that Converts Any Image into a 3D Animation
https://youtu.be/bWDFYsrjqgs

AI Voices with Human EMOTIONS (New Text to Speech)
https://youtu.be/g9YX2nWF0BM

Multi-Language Text to Speech AI (FREE multi-language ai voice genration software)
https://youtu.be/zZ2hAS7uWZk

Wellsaid Labs Full Tutorial (Best Text-to-Speech)
https://youtu.be/YwIkxXEmOBA

The Best Romantic AI Voice (Text-to-Speech AI Software)
https://youtu.be/Ui5qFkGkQeE

Text-to-Speech Comparison: Which One Sounds the Most Human?
https://youtu.be/UYMiYkSTM3k

FREE Text to Speech (AI Voice Generator) Software by MICROSOFT
https://youtu.be/CgjSOFYFvdw

The Best Cinematic AI Voice (Text-to-Speech AI Software)
https://youtu.be/d2463ynnEsM

USE ChatGPT to create images... Here is HOW !!!
https://www.youtube.com/watch?v=sJRMiT3HbQI&list=PLqQJfwY2hDK00qleSrQFLwUqvUTAFlq5V&index=4

Text to Video ... Use ChatGPT ... COMPLETE Tutorial in 4 Minutes
https://www.youtube.com/watch?v=LAy2kNd0v9Y&list=PLqQJfwY2hDK00qleSrQFLwUqvUTAFlq5V&index=5

OpenAI + Google Docs: Build Your Own AI Writer in 5 Minutes
https://www.youtube.com/watch?v=lN93GstltJ8&list=PLqQJfwY2hDK00qleSrQFLwUqvUTAFlq5V&index=7&t=115sText-to-Speech AI Videos:
-----------------------------------------------------------------------------------------
AI Voices with Human EMOTIONS (New Text to Speech)
https://youtu.be/g9YX2nWF0BM

Multi-Language Text to Speech AI (FREE multi-language ai voice genration software)
https://youtu.be/zZ2hAS7uWZk

Wellsaid Labs Full Tutorial (Best Text-to-Speech)
https://youtu.be/YwIkxXEmOBA

The Best Romantic AI Voice (Text-to-Speech AI Software)
https://youtu.be/Ui5qFkGkQeE

Secrets Revealed: Make Money with ChatGPT and Free Text-to-Speech AI by Microsoft
https://youtu.be/FFS4S1CWTqc

Text-to-Speech Comparison: Which One Sounds the Most Human?
https://youtu.be/UYMiYkSTM3k

FREE Text to Speech (AI Voice Generator) Software by MICROSOFT
https://youtu.be/CgjSOFYFvdw

The Best Cinematic AI Voice (Text-to-Speech AI Software)
https://youtu.be/d2463ynnEsM

Create website using ChatGPT... Here is HOW !!! In just 4 minutes
https://www.youtube.com/watch?v=aoh_9mNr_8g&list=PLqQJfwY2hDK00qleSrQFLwUqvUTAFlq5V&index=2&t=26s

ChatGPT & Text to Speech FREE... Watch to know HOW??? In 3 MINUTES
https://www.youtube.com/watch?v=ulaYMsF-xYk&list=PLqQJfwY2hDK00qleSrQFLwUqvUTAFlq5V&index=3

USE ChatGPT to create images... Here is HOW !!!
https://www.youtube.com/watch?v=sJRMiT3HbQI&list=PLqQJfwY2hDK00qleSrQFLwUqvUTAFlq5V&index=4

Text to Video ... Use ChatGPT ... COMPLETE Tutorial in 4 Minutes
https://www.youtube.com/watch?v=LAy2kNd0v9Y&list=PLqQJfwY2hDK00qleSrQFLwUqvUTAFlq5V&index=5

Using ChatGPT for the first time? Here is HOW !!! In 3 minutes
https://www.youtube.com/watch?v=LlW3kiulSkQ&list=PLqQJfwY2hDK00qleSrQFLwUqvUTAFlq5V&index=6

Give ChatGPT INTERNET Access ..!!!
https://www.youtube.com/watch?v=lN93GstltJ8&list=PLqQJfwY2hDK00qleSrQFLwUqvUTAFlq5V&index=7&t=115s

OpenAI + Google Docs: Build Your Own AI Writer in 5 Minutes
https://www.youtube.com/watch?v=lN93GstltJ8&list=PLqQJfwY2hDK00qleSrQFLwUqvUTAFlq5V&index=7&t=115s

Fine-tuning GPT-3.
In this video we demonstrate how to use APIs and audio to create prompts and completions that can be used to fine-tune Transformers such as GPT-3. We show how to use a News API with Python to extract news articles and create a dataset for training and fine-tuning models.

We explain what prompt and completion datasets are, and the role they play in natural language processing in fine-tuning transformers. We then discuss using video and audio streams to build data pipelines for fine-tuning and transcribing speech to text using OpenAI's Whisper.

With over 500 hours of YouTube videos being uploaded every minute video is a rich source of detailed information with which to train AI.

The video first includes step-by-step demonstrations of using the News API to create a prompt and completion dataset and then shows how to build pipelines transcribing speech to text using Whisper.

Foundation models like GPT-3 can be 'Fine-Tuned'. This Fine_tuning allows them to learn the vocabulary and semantics of particular disciplines. If you want your AI solution to be familiar with options pricing algorithms, then you can show it lots of options pricing papers. If you'd like your AI to be able to converse and write about monetary policy then you can expose it to policy papers, books on economic theory, central bank meeting minutes and news conferences.

You train transformer AI models in a particular way. You don't simply feed in a file containing the text of the book or article that you are using to train the AI. You break the text up into a series of "Prompts" and "Completions". Prompts are the beginning of a passage of text and completions are what follow a prompt.

In this post we leverage the breadth and depth of content on YouTube. We propose a strategy to use selected videos to train our AI language models. These videos are chosen because they are rich in expertise in an area we want to train our language model in. The example used in this video is to train our AI in monetary policy by studying content generated by the Federal Reserve. We devise a strategy to use speech to text transcription of YouTube videos. We use OpenAI's 'Whisper' to perform this transcription. We then break this text up into 'prompts' and completions to train our model.

Following this approach we can easily train our NLP models to have expertise in any field we choose.



#NLP #Python #FineTuning #AI #MachineLearning #NewsAPI #Whisper #Lucidate #chatgpt #gpt3 #gpt-3 #openai #whisper #openai-whisper

Links:
Attention Mechanism in Transformers: https://youtu.be/sznZ78HquPc Transformer playlist: https://youtube.com/playlist?l....ist=PLaJCKi8Nk1hwaMU
Federal reserve Description: https://youtu.be/lJTmCv2kKKs
FOMC Feb 2023 Press Conference: https://www.youtube.com/watch?v=3Iv4aCN0OOo&t=2s
Python code for Transcriber class: https://github.com/mrspiggot/p....rompts_and_completio

=========================================================================
Link to introductory series on Neural networks:
Lucidate website: https://www.lucidate.co.uk/blog/categ...

YouTube: https://www.youtube.com/playlist?list...

Link to intro video on 'Backpropagation':
Lucidate website: https://www.lucidate.co.uk/post/intro...

YouTube: https://youtu.be/8UZgTNxuKzY

'Attention is all you need' paper - https://arxiv.org/pdf/1706.03762.pdf

=========================================================================
Transformers are a type of artificial intelligence (AI) used for natural language processing (NLP) tasks, such as translation and summarisation. They were introduced in 2017 by Google researchers, who sought to address the limitations of recurrent neural networks (RNNs), which had traditionally been used for NLP tasks. RNNs had difficulty parallelizing, and tended to suffer from the vanishing/exploding gradient problem, making it difficult to train them with long input sequences.

Transformers address these limitations by using self-attention, a mechanism which allows the model to selectively choose which parts of the input to pay attention to. This makes the model much easier to parallelize and eliminates the vanishing/exploding gradient problem.

Self-attention works by weighting the importance of different parts of the input, allowing the AI to focus on the most relevant information and better handle input sequences of varying lengths. This is accomplished through three matrices: Query (Q), Key (K) and Value (V). The Query matrix can be interpreted as the word for which attention is being calculated, while the Key matrix can be interpreted as the word to which attention is paid. The eigenvalues and eigenvectors of these matrices tend to be similar, and the product of these two matrices gives the attention score.

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#ai #deeplearning #chatgpt #gpt3 #neuralnetworks #attention #attentionisallyouneed

This video shows a user how to train a GPT-2 model in Python. It requires a library called gpt-2-simple. This video trains the model on the Tiny Shakespeare set.


https://colab.research.google.....com/drive/1TCkUMfehk

Become a GPT text generation expert with our comprehensive 3-part video series. Learn how to build, train, and test your own GPT model, and gain insights into GPT-2 architecture, tokenization, and training processes that will elevate your language model projects.

Discover the power of GPT transformers and learn how to build, train, and test your own text generator in this comprehensive 3-part video series. Gain practical experience and insights into GPT-2 architecture, tokenization, and training techniques.