kvcache-ai/ktransformers
1
0
Fork 0
mirror of https://github.com/kvcache-ai/ktransformers.git synced 2026-03-14 18:37:23 +00:00
Code Issues Packages Projects Releases Wiki Activity

[docs]: update doc link (#1745)

Browse Source
This commit is contained in:
ZiWei Yuan
2025-12-24 18:00:47 +08:00
committed by GitHub
parent 3315335fb1
commit dc5feece8f
2 changed files with 2 additions and 2 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
README.md
View File

@@ -13,7 +13,7 @@
## 🎯 Overview
KTransformers is a research project focused on efficient inference and fine-tuning of large language models through CPU-GPU heterogeneous computing. The project has evolved into **two core modules**: [kt-kernel](./kt-kernel/) and [kt-sft](./kt-sft/).
KTransformers is a research project focused on efficient inference and fine-tuning of large language models through CPU-GPU heterogeneous computing. The project has evolved into **two core modules**: [kt-kernel](https://github.com/kvcache-ai/ktransformers/tree/main/kt-kernel/) and [kt-sft](https://github.com/kvcache-ai/ktransformers/tree/main/kt-sft).
## 🔥 Updates

2
kt-kernel/README.md
View File

@@ -28,7 +28,7 @@ High-performance kernel operations for KTransformers, featuring CPU-optimized Mo
**Current Support Status:**
- ✅ **Intel CPUs with AMX**: Fully supported (using weights converted to INT4/INT8 format)
- ✅ **Universal CPU (llamafile backend)**: Supported (using GGUF-format weights)
- ✅ **AMD CPUs with BLIS**: Supported (for int8 prefill & decode) - [Guide](https://github.com/kvcache-ai/ktransformers/blob/main/doc/en/kt-kernel/amd_blis)
- ✅ **AMD CPUs with BLIS**: Supported (for int8 prefill & decode) - [Guide](https://github.com/kvcache-ai/ktransformers/blob/main/doc/en/kt-kernel/amd_blis.md)
- ✅ **Kimi-K2 Native INT4 (RAWINT4)**: Supported on AVX512 CPUs (CPU-GPU shared INT4 weights) - [Guide](https://github.com/kvcache-ai/ktransformers/blob/main/doc/en/kt-kernel/Kimi-K2-Thinking-Native.md)
- ✅ **FP8 weights (e.g., MiniMax-M2.1)**: Supported on AVX512 CPUs (CPU-GPU shared FP8 weights) - [Guide](https://github.com/kvcache-ai/ktransformers/blob/main/doc/en/kt-kernel/MiniMax-M2.1-Tutorial.md)