Although, tbf, some libraries are documented better than others.
Also, local llms with an agentic tool can be a lot of fun to quickly prototype things. Quality can be hit or miss.
Hopefully the work trickles down to local models long-term.
Also, local llms with an agentic tool can be a lot of fun to quickly prototype things. Quality can be hit or miss.
Hopefully the work trickles down to local models long-term.
Obviously, if the library or code using it weren't part of the training data, and you don't supply either in the context of your request, then it won't generate valid code for it. But that's not LLM's fault.
You can imagine the classic attention mechanism as a lookup table, actually.
Transformers are layers and layers and layers of lookup tables.