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empower-dev/llama3-empower-functions-large-v1.1

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face

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Model Card

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		Balance in accuracy and cost
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