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Exa - Pytorch

Project description

Multi-Modality

Exa

Boost your GPU's LLM performance by 300% on everyday GPU hardware, as validated by renowned developers, in just 5 minutes of setup and with no additional hardware costs.


Principles

  • Radical Simplicity (Utilizing super-powerful LLMs with as minimal lines of code as possible)
  • Ultra-Optimizated Peformance (High Performance code that extract all the power from these LLMs)
  • Fludity & Shapelessness (Plug in and play and re-architecture as you please)

📦 Installation 📦

$ pip3 install exxa

Usage

🎉 Features 🎉

  • World-Class Quantization: Get the most out of your models with top-tier performance and preserved accuracy! 🏋️‍♂️

  • Automated PEFT: Simplify your workflow! Let our toolkit handle the optimizations. 🛠️

  • LoRA Configuration: Dive into the potential of flexible LoRA configurations, a game-changer for performance! 🌌

  • Seamless Integration: Designed to work seamlessly with popular models like LLAMA, Falcon, and more! 🤖


💌 Feedback & Contributions 💌

We're excited about the journey ahead and would love to have you with us! For feedback, suggestions, or contributions, feel free to open an issue or a pull request. Let's shape the future of fine-tuning together! 🌱

Check out our project board for our current backlog and features we're implementing

License

MIT

Todo

  • Setup utils logger classes for metric logging with useful metadata such as token inference per second, latency, memory consumption
  • Add cuda c++ extensions for radically optimized classes for high performance quantization + inference on the edge

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