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hackerllama - The Random Transformer

Understand how transformers work by demystifying all the math behind them ....

Illustrated Transformer , Machine Learning , Deep Learning , Ilustrated Transformer , Random Encoder Decoder ,

The Illustrated GPT-2 (Visualizing Transformer Language Models)

Discussions:
Hacker News (64 points, 3 comments), Reddit r/MachineLearning (219 points, 18 comments)

Translations: Simplified Chinese, French, Korean, Russian, Turkish

This year, we saw a dazzling application of machine learning. The OpenAI GPT-2 exhibited impressive ability of writing coherent and passionate essays that exceed what we anticipated current language models are able to produce. The GPT-2 wasn’t a particularly novel architecture – it’s architecture is very similar to the decoder-only transformer. The GPT2 was, however, a very large, transformer-based language model trained on a massive dataset. In this post, we’ll look at the architecture that enabled the model to produce its results. We will go into the depths of its self-attention layer. And then we’ll look at applications for the decoder-only transformer beyond language modeling.

My goal here is to also supplement my earlier post, The Illustrated Transformer, ....

Mohammad Saleh , Ryan Sepassi , Lukasz Kaiser , Peterj Liu , Neural Network , Hacker News , Simplified Chinese , Illustrated Transformer , Brain Surgery , Looking Inside , Language Modeling , Illustrated Word , Generating Wikipedia , Summarizing Long Sequences , Character Level Language Modeling , Deeper Self Attention , First Law , Byte Pair Encoding , Illustrated Self Attention , Processing One Token , Connected Neural Network , Beyond Language Modeling , Sample Efficient Text Summarization Using , Single Pre Trained Transformer , Music Transformer , Hugging Face ,

GitHub - mlabonne/llm-course: Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks. - GitHub - mlabonne/llm-course: Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks. ....

Romano Roth , Andrej Karpathy , Rachael Tatman , Thomas Thelen , Jay Alammar , Lilian Weng , Google Colab , Fastest Library To , Neural Networks , Recurrent Neural Networks Rnns , A Survey On Evaluation , Large Language Model , Fastest Library , Large Language , Science Libraries , Learning Libraries , Mean Squared Error , Gradient Descent , Stochastic Gradient Descent , Multilayer Perceptron , Language Processing , Extraction Techniques , Term Frequency Inverse Document , Illustrated Transformer , Performance Computing , Policy Optimization ,

I made a transformer by hand (no training!)

To better understand how transformers work, I hand-assigned all the weights to predict a simple sequence. ....

Susan Vogel , Illustrated Transformer , Attention Is All You ,

Ask HN: Can someone ELI5 Transformers and the "Attention is all we need" paper

Ask HN: Can someone ELI5 Transformers and the "Attention is all we need" paper
ycombinator.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from ycombinator.com Daily Mail and Mail on Sunday newspapers.

Paul Graham , Geoffrey Hinton , Ilya Sutskever , John Carmack , All You , Illustrated Transformer , Head Attention ,