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Browse files- Dockerfile +57 -0
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FROM pytorch/pytorch:2.0.1-cuda11.7-cudnn8-runtime
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ENV DEBIAN_FRONTEND=noninteractive
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# Set the MKL_THREADING_LAYER environment variable to GNU
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ENV MKL_THREADING_LAYER=GNU
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# Install Git, OpenGL libraries, and libglib2.0
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RUN apt-get update && apt-get install -y git libgl1-mesa-glx libglib2.0-0
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RUN apt-get update && apt-get install -y ninja-build
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# Install necessary dependencies, including CMake, a C++ compiler, and others
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RUN apt-get update && apt-get install -y unzip ffmpeg cmake g++ build-essential aria2
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# Set up a new user named "user" with user ID 1000
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RUN useradd -m -u 1000 user
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# Switch to the "user" user
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USER user
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# Set environment variables
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ENV HOME=/home/user \
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CUDA_HOME=/usr/local/cuda \
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PATH=/home/user/.local/bin:$PATH \
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LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH} \
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LIBRARY_PATH=${CUDA_HOME}/lib64/stubs:${LIBRARY_PATH} \
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PYTHONPATH=$HOME/app \
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PYTHONUNBUFFERED=1 \
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GRADIO_ALLOW_FLAGGING=never \
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GRADIO_NUM_PORTS=1 \
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GRADIO_SERVER_NAME=0.0.0.0 \
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GRADIO_THEME=huggingface \
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GRADIO_SHARE=False \
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SYSTEM=spaces
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# Set the working directory to the user's home directory
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WORKDIR $HOME/app
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# Clone your repository or add your code to the container
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RUN git clone -b main https://github.com/fffiloni/MiniGPT4-video $HOME/app
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# Install dependencies
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#COPY requirements.txt $HOME/app/requirements.txt
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RUN pip install --no-cache-dir -r requirements.txt
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RUN mkdir checkpoints
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# Download checkpoint files using aria2
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RUN aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/Vision-CAIR/MiniGPT4-Video/resolve/main/checkpoints/video_llama_checkpoint_last.pth -d $HOME/app/checkpoints -o video_llama_checkpoint_last.pth
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# Set the environment variable to specify the GPU device
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ENV CUDA_DEVICE_ORDER=PCI_BUS_ID
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ENV CUDA_VISIBLE_DEVICES=0
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# Run your app.py script
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CMD ["python", "minigpt4_video_demo.py"]
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