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this is cool, thanks for starting down this path with PyTorch. I came here from the HN discussion. I have been focusing on llama 2 since it seems for me to be a bit of a tipping point and its time to dig into local LLMs.
So lets say I want to limit the output of llama to valid Python code? The python grammar seems no longer to be EBNF but rather PEG. I was thinking that for my purposes I would actually be very happy if the LLM output was constrained to valid python AST. Either of these requires a different parser and thus code to handle each case.
Have you thought about how to handle this potential proliferation of parser formats? I am probably going to try to copy your approach and extend this to handle python AST.
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