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[docs]: Update README with Python 3.12 and dependency changes (#1634)
Updated Python version in installation instructions and adjusted KTransformers and flash-attention wheel filenames accordingly.
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kt-sft/README.md

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@@ -111,7 +111,7 @@ According to the following example, install both the **KTransformers** and **LLa
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```shell
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# 1. Create a conda environment
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conda create -n Kllama python=3.10 # choose from : [3.10, 3.11, 3.12, 3.13]
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conda create -n Kllama python=3.12 # choose from : [3.10, 3.11, 3.12, 3.13]
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conda install -y -c conda-forge libstdcxx-ng gcc_impl_linux-64
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# ATTENTION: DO NOT skip this step, even if your cuda version is not 11.8! Otherwise, you will get this error: ImportError: libcudart.so.11.0: cannot open shared object file: No such file or directory.
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conda install -y -c nvidia/label/cuda-11.8.0 cuda-runtime
@@ -121,11 +121,11 @@ git clone --depth 1 https://github.com/hiyouga/LLaMA-Factory.git
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cd LLaMA-Factory
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pip install -e ".[torch,metrics]" --no-build-isolation
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# 3. Install the KTransformers wheel that matches your Torch and Python versions (Note: The CUDA version can differ from that in the wheel filename.)
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pip install ktransformers-0.4.1+cu128torch28fancy-cp310-cp310-linux_x86_64.whl
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# 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.)
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pip install ktransformers-0.4.1+cu128torch27fancy-cp312-cp312-linux_x86_64.whl
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# 4. Install flash-attention, download the corresponding file based on your Python and Torch versions from: https://github.com/Dao-AILab/flash-attention/releases
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pip install https://github.com/Dao-AILab/flash-attention/releases/download/v2.8.3/flash_attn-2.8.3+cu12torch2.8cxx11abiTRUE-cp310-cp310-linux_x86_64.whl
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pip install flash_attn-2.8.3+cu12torch2.7cxx11abiTRUE-cp312-cp312-linux_x86_64.whl
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# abi=True/False can find from below
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# import torch
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# print(torch._C._GLIBCXX_USE_CXX11_ABI)

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