|
--- |
|
license: apache-2.0 |
|
base_model: |
|
- meta-llama/Meta-Llama-3.1-8B-Instruct |
|
tags: |
|
- function |
|
- function-calling |
|
- tool-using |
|
--- |
|
|
|
## Empower Functions Model v1.1 |
|
|
|
 |
|
|
|
[https://github.com/empower-ai/empower-functions](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](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B) | [model](https://huggingface.co/empower-dev/llama3-empower-functions-small-v1.1), [gguf](https://huggingface.co/empower-dev/llama3-empower-functions-small-gguf-v1.1) | Most cost-effective, locally runnable | | Balance in accuracy and cost | |
|
| llama3-empower-functions-large | 128k context, based on [Llama3.1 70B](https://huggingface.co/meta-llama/Meta-Llama-3.1-70B) | [model](https://huggingface.co/empower-dev/llama3-empower-functions-large-v1.1) | 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](https://github.com/empower-ai/empower-functions?tab=readme-ov-file#prompt-raw-model), run it [locally](https://github.com/empower-ai/empower-functions?tab=readme-ov-file#running-locally) through llama-cpp-python, or use our [hosted API](https://github.com/empower-ai/empower-functions?tab=readme-ov-file#using-empower-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: |
|
|
|
 |
|
(captured on Sep 10, 2024) |
|
|
|
## Demo App |
|
Check our healthcare appointment booking [demo](https://app.empower.dev/chat-demo) |
|
|
|
Want to customize the model? Please contact us at [founders@empower.dev](mailto:founders@empower.dev) |
|
Hyper Icon |
