Empower Functions is a family of LLMs(large language models) that offer GPT-4 level capabilities for real-world "tool using" use cases, with full compatibility support to serve as a drop-in replacement.
Key Features
Automatic tool using, able to decide when to use tools and when to converse, optimized for long conversations
Parallel call, supports calling one function multiple times, multiple functions, or a combination of both
Sequential calling, supports calling multiple functions sequentially to fulfill the user request
We have tested and the family of models in following setup:
empower-functions-small: fp16 on 1xA100 40G, GGUF and 4bit GGUF on Macbook M2 Pro with 32G RAM, in minimal the 4bit GGUF version requires 7.56G RAM.
empower-functions-medium: fp16 on 2xA100 80G
empower-functions-large: fp16 on 4xA100 80G
Usage
There are three ways to use the empower-functions model. You can either directly prompt the raw model, run it locally through llama-cpp-python, or use our hosted API
Evaluation
v1.1 is the newer version trained based on meta llama3.1 with the newly updated dataset, it has achieved state-of-the-art performance on the Berkeley Function Calling leaderboard:
