[feature] update docker image and entrypoint

Dockerfile

@@ -32,4 +32,4 @@ CPU_INSTRUCT=NATIVE  KTRANSFORMERS_FORCE_BUILD=TRUE TORCH_CUDA_ARCH_LIST="8.0;8.
 pip cache purge
 EOF
 
-ENTRYPOINT [ "/opt/conda/bin/ktransformers" ]
+ENTRYPOINT ["tail", "-f", "/dev/null"]

doc/en/Docker.md

@@ -7,7 +7,7 @@
 ## Images
 There is a Docker image available for our project, you can pull the docker image by：
 ```
-docker pull approachingai/ktransformers:0.1.1
+docker pull approachingai/ktransformers:0.2.1
 ```
 **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.
 
@@ -16,14 +16,16 @@ docker pull approachingai/ktransformers:0.1.1
 
  - finish, execute
    ```bash
-   docker build  -t approachingai/ktransformers:v0.1.1 .
+   docker build  -t approachingai/ktransformers:0.2.1 .
    ```
 
 ## Usage
 
 Assuming you have the [nvidia-container-toolkit](https://github.com/NVIDIA/nvidia-container-toolkit) that you can use the GPU in a Docker container.
 ```
-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
+docker run --gpus all -v /path/to/models:/models --name ktransformers -itd approachingai/ktransformers:0.2.1
+docker exec -it ktransformers /bin/bash
+python -m ktransformers.local_chat  --gguf_path /models/path/to/gguf_path --model_path /models/path/to/model_path --cpu_infer 33
 ```
 
 More operators you can see in the [readme](../../README.md)

ktransformers/__init__.py

@@ -5,7 +5,7 @@
 Author       : kkk1nak0
 Date         : 2024-08-15 07:34:46
 Version      : 1.0.0
-LastEditors  : unicornchan 
-LastEditTime : 2025-02-10 00:59:53
+LastEditors  : chenxl 
+LastEditTime : 2025-02-15 03:53:02
 '''
-__version__ = "0.2.0"
+__version__ = "0.2.1"