An awesome tool/library benchmark LLM performance on all kinds of hardware!
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Table of Contents
Installation with pip is simple as follows:
pip install impetus
For more examples, please refer to the Documentation
This project use poetry for dependency management, and is required for running impetus locally.
- Clone the repo
git clone https://github.com/dhmnr/impetus.git
- Install Dependencies
poetry install
- Run the command as follows
poetry shell run impetus --help
- Support Quantization
- Multiple GPU support with accelerate
- GPU/CPU usage information
- Flops/MFU information
- Detailed breakdown, | self-attention | FFN | lm_head
- Support BERT and VLMs and others
- Support different backends
- Support different datasets
See the open issues for a full list of proposed features (and known issues).
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Distributed under the MIT License. See LICENSE for more information.
Project Link: https://github.com/dhmnr/impetus
Use this space to list resources you find helpful and would like to give credit to. I've included a few of my favorites to kick things off!