Text environments, LLMs with tools and agents!
Text environments provide a learning ground for language agents. It allows a language model to use tools to accomplish a task such as using a Python interpreter to answer math questions or using a search index for trivia questions. Having access to tools allows language models to solve tasks that would be very hard for the models itself but can be trivial for the appropriate tools.
We are excited to bring to the community a complete set of functionalities and full examples to train LLMs to use tools!
Check out the documentation page here and few examples below:
- fine tune a LLM to learn to use a simple calculator tool
- fine tune a LLM to learn to use a Question Answering tool to answer general knowledge questions
- fine tune a LLM to learn to use a Python interpreter
What's Changed
- Release: v0.6.0 by @younesbelkada in #684
- set dev version by @younesbelkada in #685
- [DPO] fix DPO ref_model=None by @kashif in #703
- [Docs] fix example README.md by @kashif in #705
- TextEnvironments by @lvwerra in #424
Full Changelog: v0.6.0...v0.7.0