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Merge pull request #317 from kvcache-ai/develop-0.2.1
[feature] update docker image and entrypoint
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Dockerfile

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pip cache purge
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EOF
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ENTRYPOINT [ "/opt/conda/bin/ktransformers" ]
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ENTRYPOINT ["tail", "-f", "/dev/null"]

doc/en/Docker.md

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## Images
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There is a Docker image available for our project, you can pull the docker image by:
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```
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docker pull approachingai/ktransformers:0.1.1
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docker pull approachingai/ktransformers:0.2.1
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```
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**Notice**: In this image, we compile the ktransformers in AVX512 instuction CPUs, if your cpu not support AVX512, it is suggested to recompile and install ktransformer in the /workspace/ktransformers directory within the container.
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- finish, execute
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```bash
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docker build -t approachingai/ktransformers:v0.1.1 .
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docker build -t approachingai/ktransformers:0.2.1 .
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```
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## Usage
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Assuming you have the [nvidia-container-toolkit](https://github.com/NVIDIA/nvidia-container-toolkit) that you can use the GPU in a Docker container.
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```
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docker run --gpus all -v /path/to/models:/models -p 10002:10002 approachingai/ktransformers:v0.1.1 --port 10002 --gguf_path /models/path/to/gguf_path --model_path /models/path/to/model_path --web True
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docker run --gpus all -v /path/to/models:/models --name ktransformers -itd approachingai/ktransformers:0.2.1
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docker exec -it ktransformers /bin/bash
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python -m ktransformers.local_chat --gguf_path /models/path/to/gguf_path --model_path /models/path/to/model_path --cpu_infer 33
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```
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More operators you can see in the [readme](../../README.md)

ktransformers/__init__.py

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Author : kkk1nak0
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Date : 2024-08-15 07:34:46
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Version : 1.0.0
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LastEditors : unicornchan
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LastEditTime : 2025-02-10 00:59:53
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LastEditors : chenxl
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LastEditTime : 2025-02-15 03:53:02
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'''
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__version__ = "0.2.0"
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__version__ = "0.2.1"

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