From 1c08a4f0fbcccc0c117b5332e58a3406bd83c4c4 Mon Sep 17 00:00:00 2001
From: JimmyPeilinLi <lipeilin@mail.nwpu.edu.cn>
Date: Sat, 8 Nov 2025 08:54:32 +0000
Subject: [PATCH] fix: remove py310 as guide

---
 doc/en/KTransformers-Fine-Tuning_User-Guide.md    | 6 +++---
 doc/zh/KTransformers-Fine-Tuning_User-Guide_zh.md | 6 +++---
 ktransformers/__init__.py                         | 2 +-
 3 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/doc/en/KTransformers-Fine-Tuning_User-Guide.md b/doc/en/KTransformers-Fine-Tuning_User-Guide.md
index 822ac53b..651f7c17 100644
--- a/doc/en/KTransformers-Fine-Tuning_User-Guide.md
+++ b/doc/en/KTransformers-Fine-Tuning_User-Guide.md
@@ -111,7 +111,7 @@ According to the following example, install both the **KTransformers** and **LLa
 
 ```shell
 # 1. Create a conda environment
-conda create -n Kllama python=3.10 # choose from : [3.10, 3.11, 3.12, 3.13]
+conda create -n Kllama python=3.12 # choose from : [3.10, 3.11, 3.12, 3.13]
 conda install -y -c conda-forge libstdcxx-ng gcc_impl_linux-64
 conda install -y -c nvidia/label/cuda-11.8.0 cuda-runtime
 
@@ -121,10 +121,10 @@ cd LLaMA-Factory
 pip install -e ".[torch,metrics]" --no-build-isolation
 
 # 3. Install the KTransformers wheel that matches your Torch and Python versions, from https://github.com/kvcache-ai/ktransformers/releases/tag/v0.4.1 (Note: The CUDA version can differ from that in the wheel filename.)
-pip install ktransformers-0.4.1+cu128torch28fancy-cp310-cp310-linux_x86_64.whl
+pip install ktransformers-0.4.1+cu128torch27fancy-cp312-cp312-linux_x86_64.whl
 
 # 4. Install flash-attention, download the corresponding file based on your Python and Torch versions from: https://github.com/Dao-AILab/flash-attention/releases
-pip install flash_attn-2.8.3+cu12torch2.8cxx11abiTRUE-cp310-cp310-linux_x86_64.whl
+pip install flash_attn-2.8.3+cu12torch2.7cxx11abiTRUE-cp312-cp312-linux_x86_64.whl
 # abi=True/False can find from below
 # import torch
 # print(torch._C._GLIBCXX_USE_CXX11_ABI)
diff --git a/doc/zh/KTransformers-Fine-Tuning_User-Guide_zh.md b/doc/zh/KTransformers-Fine-Tuning_User-Guide_zh.md
index 0d24288a..f7c301f6 100644
--- a/doc/zh/KTransformers-Fine-Tuning_User-Guide_zh.md
+++ b/doc/zh/KTransformers-Fine-Tuning_User-Guide_zh.md
@@ -105,7 +105,7 @@
 
 ```shell
 # 1. 安装conda环境
-conda create -n Kllama python=3.10 # choose from : [3.10, 3.11, 3.12, 3.13]
+conda create -n Kllama python=3.12 # choose from : [3.11, 3.12, 3.13]
 conda install -y -c conda-forge libstdcxx-ng gcc_impl_linux-64
 conda install -y -c nvidia/label/cuda-11.8.0 cuda-runtime
 
@@ -115,10 +115,10 @@ cd LLaMA-Factory
 pip install -e ".[torch,metrics]" --no-build-isolation
 
 # 3. 安装对应torch和python版本的KTransformers（CUDA版本可以跟whl命名的不一致），从https://github.com/kvcache-ai/ktransformers/releases/tag/v0.4.1
-pip install ktransformers-0.4.1+cu128torch28fancy-cp310-cp310-linux_x86_64.whl
+pip install ktransformers-0.4.1+cu128torch27fancy-cp312-cp312-linux_x86_64.whl
 
 # 4. 安装flash-attention，参照python版本和torch版本，从https://github.com/Dao-AILab/flash-attention/releases下载
-pip install flash_attn-2.8.3+cu12torch2.8cxx11abiTRUE-cp310-cp310-linux_x86_64.whl
+pip install flash_attn-2.8.3+cu12torch2.7cxx11abiTRUE-cp312-cp312-linux_x86_64.whl
 # abi=True/False可以用下面代码查看
 # import torch
 # print(torch._C._GLIBCXX_USE_CXX11_ABI)
diff --git a/ktransformers/__init__.py b/ktransformers/__init__.py
index e2884473..59cad5ee 100644
--- a/ktransformers/__init__.py
+++ b/ktransformers/__init__.py
@@ -8,4 +8,4 @@
 LastEditors  : chenxl 
 LastEditTime : 2025-02-15 03:53:02
 '''
-__version__ = "0.3.2"
+__version__ = "0.4.1"