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…So you’re trying to always build an LLM that’s going to fit on one GPU? Yes. Most of the examples I have fit on one GPU. I have some bonus materials on some MoE models; one or two of them may require multiple GPUs, but the goal is to have it on one GPU. And the beautiful thing is also you can self-verify. It’s almost like RLVR. When you code these from scratch, you can take an existing model from the Hugging Face Transformers library. The Hugging Face Transformers library is great, but if you want to learn about LLMs, I think that’s not the best place to start because the code is so complex. It has to fit so many use cases and some people use it in production. It has to be really sophisticated, so it’s intertwined and hard; it’s not linear to read. It started as a fine-tuning library, and then it grew to be the standard representation of every model architecture and the way it is loaded. Hugging Face is the default place to get a model, and Transformers is the software that enables it— —so people can easily load a model— —and do something basic with it.…

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