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Comment by QuadrupleA | Hacker News Reader

Doesn't huggingface have dozens of freely available pretrained models like this (including various sized implementations of GPT2) and isn't the source available on most if you wanted to train them yourself?

All I see in the comments is praise for the author as a person, so just wondering what's unique about this that's not available elsewhere? 730 upvotes and counting, assuming I'm missing something...

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True, but the use cases arent the same. As he did before for other models, he has a knack for distilling the code down to beautiful, self-contained examples of high didactic value.

It's an order of magnitude easier to grok the basics from this repo than from going through (admittedly more ergonomic or performant or production-ready) huggingface repos.

Additionally, in terms of the streamlining nanoGPT porports, HuggingFace's implementations play nice with optimization techniques such as ONNX/TensorRT, which will give you better performance than anything PyTorch-based even if minimal.

That doesn't mean an ONNX-ed nanoGPT won't be better, but the field of optimized text generation isn't as new as people claim.

This is a didactic implementation. If you read the HuggingFace repo it is much more abstracted on account they implement many models in the same codebase. It's not fast or big, just easier to read and tweak.

If so, then why the second line of its documentation says that "it is a rewrite of minGPT that prioritizes teeth over education"?

minGPT prioritized being understandable above all else, and was not very fast. This repo includes several optimizations, but it still much more understandable than probably any other open source implementation.

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