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--- |
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license: apache-2.0 |
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base_model: |
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- empower-dev/llama3-empower-functions-small-v1.1 |
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tags: |
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- function |
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- function-calling |
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- tool-using |
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--- |
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## Empower Functions Model v1.1 |
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/6424a49f12ba34f9894ab9b7/wXkYX_NXEFtpmBsQd6nIV.png) |
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[https://github.com/empower-ai/empower-functions](https://github.com/empower-ai/empower-functions) |
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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. |
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## Key Features |
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* Automatic tool using, able to decide when to use tools and when to converse, optimized for long conversations |
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* Parallel call, supports calling one function multiple times, multiple functions, or a combination of both |
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* Sequential calling, supports calling multiple functions sequentially to fulfill the user request |
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* Streaming |
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## Family of Models |
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| Model | Specs | Links | Notes | |
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| ------------------------------ | ------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------- | |
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| 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 | |
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| 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 | |
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### Hardware Requirement |
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We have tested and the family of models in following setup: |
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- 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. |
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- empower-functions-medium: fp16 on 2xA100 80G |
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- empower-functions-large: fp16 on 4xA100 80G |
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## Usage |
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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) |
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## Evaluation |
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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: |
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/6570b927f56f953867847255/HrzbI0vmyvYhabS-I5hGj.png) |
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(captured on Sep 10, 2024) |
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## Demo App |
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Check our healthcare appointment booking [demo](https://app.empower.dev/chat-demo) |
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Want to customize the model? Please contact us at [[email protected]](mailto:[email protected]) |
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