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polymutex
@polymutex.eth
One issue with coding with LLMs is that they use old versions of libraries or packages. Not always possible to prompt them out of it. What do usually you do about this?
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@m-j-r
maybe abliteration can help? https://huggingface.co/blog/mlabonne/abliteration @z0r0z & @nerderlyne might know.
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polymutex
@polymutex.eth
This looks interesting but seems like it needs to be done as a training step. I'm looking for a solution on already-trained code generation models. Additionally, abliteration is about removing a part of the LLM, whereas when an LLM uses an old library it's (sometimes) due to lack of knowledge about the new version.
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@m-j-r
w/o domain-specific pretraining like how nvidia tried it (will find the link), isn't this throwing down the "OOD w/o a model" guantlet? the recent libraries show up in the index of snippets the model (or user) is retrieving, whether it's weights, pastebin, or git. w/ recency bias, at least the user is reducing some lookup cost for weights. has embodied CoT changed this experience for you? agents should first & foremost recognize generative errors, conserving resources by lookups right behind it. https://warpcast.com/nerderlyne/0x335ecb47
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polymutex
@polymutex.eth
I'm actually not sure, which is part of the problem. Concrete example: I once asked Claude to generate code in Rust, and it did so using an old version of a crate. Then I ask to use the newest version of the crate (with its number). It returns an updated Cargo.toml, file but only changes some callsites to the new API.
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polymutex
@polymutex.eth
Did it truly know about the new version of the crate? The edits to the old-version callsites it made were correct in isolation, but it left others that were still using the old version API. Or did it understand that the new version was out of its knowledge, then made up a new API that happened to be partially correct?
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