🎉 Introduction
KTransformers, pronounced as Quick Transformers, is designed to enhance your 🤗 Transformers experience with advanced kernel optimizations and placement/parallelism strategies.KTransformers is a flexible, Python-centric framework designed with extensibility at its core. By implementing and injecting an optimized module with a single line of code, users gain access to a Transformers-compatible interface, RESTful APIs compliant with OpenAI and Ollama, and even a simplified ChatGPT-like web UI.
Our vision for KTransformers is to serve as a flexible platform for experimenting with innovative LLM inference optimizations. Please let us know if you need any other features.
🔥 Updates
- Feb 10, 2025: Support Deepseek-R1 and V3 on single (24GB VRAM)/multi gpu and 382G DRAM, up to 3~28x speedup. The detailed tutorial is here.
- Aug 28, 2024: Support 1M context under the InternLM2.5-7B-Chat-1M model, utilizing 24GB of VRAM and 150GB of DRAM. The detailed tutorial is here.
- Aug 28, 2024: Decrease DeepseekV2's required VRAM from 21G to 11G.
- Aug 15, 2024: Update detailed TUTORIAL for injection and multi-GPU.
- Aug 14, 2024: Support llamfile as linear backend.
- Aug 12, 2024: Support multiple GPU; Support new model: mixtral 8*7B and 8*22B; Support q2k, q3k, q5k dequant on gpu.
- Aug 9, 2024: Support windows native.