Chitu: High-Performance Inference Framework
Chitu is a cutting-edge inference framework designed specifically for large language models. It emphasizes three core principles:
- Efficiency: Continuous development and integration of the latest optimizations for large language models, including GPU kernels, parallel strategies, and quantizations.
- Flexibility: Support for a wide range of hardware environments, including legacy GPUs, non-NVIDIA GPUs, and CPUs, making it versatile for diverse deployment requirements.
- Availability: Ready for real-world production, ensuring that users can deploy models effectively.
Key Features:
- Supports various mainstream large language models, including DeepSeek, LLaMA series, and Mixtral.
- Offers CPU+GPU hybrid inference capabilities.
- Provides efficient operators with online FP8 to BF16 conversion.
- Comprehensive performance testing tools available.
Benefits:
- Improved output speed and efficiency, especially in memory bandwidth utilization.
- Designed for professional users and developers with detailed installation guides and support.
Highlights:
- Active community contributions and discussions.
- Apache License v2.0, ensuring open-source accessibility.
