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lewtun

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PyTorch OpenEnv

github.com
1 points·by lewtun·9 miesięcy temu·0 comments

Scaling Laws for Reinforcement Learning

huggingface.co
1 points·by lewtun·9 miesięcy temu·0 comments

comments

lewtun
·2 miesiące temu·discuss
Shameless plug: https://huggingface.co/spaces/smolagents/ml-intern

It’s a simple harness around Opus, but with tight integration to Hugging Face infra, so the agent can read papers, test code and launch experiments
lewtun
·3 miesiące temu·discuss
Hugging Face Buckets are pretty simple: https://huggingface.co/docs/huggingface_hub/en/guides/bucket...

Disclaimer: I work at HF
lewtun
·8 miesięcy temu·discuss
The analogy stems from the notion that neural nets are "grown" rather than "engineered". Chris Olah has an old, but good post with some specific examples: https://colah.github.io/notes/bio-analogies/
lewtun
·8 miesięcy temu·discuss
Thanks! I expect the book will remain relevant as long as the Transformers architecture does. That’s why we mostly focus on topics we think will stand the test of time, but let’s see how that plays out :)
lewtun
·8 miesięcy temu·discuss
In the specific case of SmolLM, it originates from the meme in this dataset https://huggingface.co/datasets/bigcode/the-stack-smol
lewtun
·8 miesięcy temu·discuss
Hi, Lewis here (one of the co-authors). Happy to answer any questions people have about the book :)
lewtun
·9 miesięcy temu·discuss
For those interested in playing with an implementation of these ideas, my colleagues at HF made some recipes here: https://github.com/huggingface/trl/blob/main/docs/source/lor...
lewtun
·10 miesięcy temu·discuss
“QED and the Men Who Made It” [1] might be close to what you’re after for quantum theory at least. Unlike other popular accounts, it gets quite technical and covers a lot of the historical dead ends that people had during the development of quantum field theory.

[1] https://press.princeton.edu/books/paperback/9780691033273/qe...