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Empower Functions Model v1.1

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https://github.com/empower-ai/empower-functions

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
  • Streaming

Family of Models

Model Specs Links Notes
llama3-empower-functions-small 128k context, based on Llama3.1 8B model, gguf Most cost-effective, locally runnable
llama3-empower-functions-large 128k context, based on Llama3.1 70B model Best accuracy

Hardware Requirement

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:

image/png (captured on Sep 10, 2024)

Demo App

Check our healthcare appointment booking demo

Want to customize the model? Please contact us at founders@empower.dev

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