GPT-1 | Paper Explained & PyTorch Implementation

Improving Language Understanding by Generative Pre-Training(GPT) is the first model by OpenAI which leverages self-supervised learning and uses a transformer architecture. Paper: https://s3-us-west-2.amazonaws.com/op... ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ GitHub Repos: https://github.com/maciejbalawejder/D... https://github.com/lyeoni/gpt-pytorch - training ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Connect with me on: Linkedin -   / maciej-balawejder-rt8015   GitHub - https://github.com/maciejbalawejder Medium -   / maciejbalawejder   Buy Me a Coffee - [https://www.buymeacoffee.com/mbalawejder](https://www.buymeacoffee.com/mbalawejder) ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Timestamps: 0:00 Introduction 1:00 GPT 2:15 Self-Supervised Learning 3:35 Loss functions 4:30 Architecture 5:17 Textual Entailment 6:17 Question Answering 7:12 Semantic Similarity 8:13 Classification 9:30 Model Specifications 11:55 Conclusions 12:30 PyTorch Implementation 13:30 Decoder Layer 15:30 GPT Architecture 16:42 Language Modelling Head 17:11 Classification Head

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(Image-GPT) Generative Pretraining from Pixels | Paper Explained + Colab Notebook
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(Image-GPT) Generative Pretraining from Pixels | Paper Explained + Colab Notebook

Let's build the GPT Tokenizer
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Let's build the GPT Tokenizer

(GPT-2) Language Models are Unsupervised Multitask Learners | Paper Explained
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(GPT-2) Language Models are Unsupervised Multitask Learners | Paper Explained

Visualizing transformers and attention | Talk for TNG Big Tech Day '24
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Visualizing transformers and attention | Talk for TNG Big Tech Day '24

Let's build GPT: from scratch, in code, spelled out.
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Let's build GPT: from scratch, in code, spelled out.

1: Introduction to Neural Networks and Deep Learning; Training Deep NNs
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1: Introduction to Neural Networks and Deep Learning; Training Deep NNs

GPT-3: Language Models are Few-Shot Learners (Paper Explained)
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GPT-3: Language Models are Few-Shot Learners (Paper Explained)

Transformers, the tech behind LLMs | Deep Learning Chapter 5
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Transformers, the tech behind LLMs | Deep Learning Chapter 5

Minimum Viable Generative Pre-trained Transformer (mvGPT)
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Minimum Viable Generative Pre-trained Transformer (mvGPT)

Yann LeCun's $1B Bet Against LLMs [Part 1]
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Yann LeCun's $1B Bet Against LLMs [Part 1]

AI, Machine Learning, Deep Learning and Generative AI Explained
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AI, Machine Learning, Deep Learning and Generative AI Explained

LSTM is dead. Long Live Transformers!
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LSTM is dead. Long Live Transformers!

Intuition behind Mamba and State Space Models | Enhancing LLMs!
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Intuition behind Mamba and State Space Models | Enhancing LLMs!

Stanford CS229 I Machine Learning I Building Large Language Models (LLMs)
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Stanford CS229 I Machine Learning I Building Large Language Models (LLMs)

GPT-3 - Language Models are Few-Shot Learners | Paper Explained
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GPT-3 - Language Models are Few-Shot Learners | Paper Explained

What are Transformer Models and how do they work?
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What are Transformer Models and how do they work?

Inception(GoogLeNet) | Paper Explained & PyTorch Implementation
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Inception(GoogLeNet) | Paper Explained & PyTorch Implementation

State of GPT | BRK216HFS
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State of GPT | BRK216HFS

But what is a neural network? | Deep learning chapter 1
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But what is a neural network? | Deep learning chapter 1

Yann LeCun | Self-Supervised Learning, JEPA, World Models, and the future of AI
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Yann LeCun | Self-Supervised Learning, JEPA, World Models, and the future of AI