Related to #34.This would be the holy grail for this maintainer, but implied in this is that we would need a trained local model, since local models are terrible with the tasks we need unless fine-tuned (from previous experiments). However, fine-tuning takes GPU resources and dedicated developer time, which we currently don't have. But a local model potentially has these advantages:
Lower latency for users than with web service-based model providers (though tokens/minute can vary a lot depending on local model training and local hardware).
Avoid third-party model provider downtime. This can happen quite often with ChatGPT.
@anngvu IDK if you have seen this (or maybe you introduced me to this...can't recall) but this might be a nice playground to experiment with local LLMs https://lmstudio.ai/
Related to #34.This would be the holy grail for this maintainer, but implied in this is that we would need a trained local model, since local models are terrible with the tasks we need unless fine-tuned (from previous experiments). However, fine-tuning takes GPU resources and dedicated developer time, which we currently don't have. But a local model potentially has these advantages: