Create Dockerfile

Dockerfile

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+# Use an official NVIDIA CUDA base image, which is great for PyTorch and GPU-heavy tasks
+FROM pytorch/pytorch:2.1.0-cuda12.1-cudnn8-runtime
+
+# Set the working directory in the container
+WORKDIR /code
+
+# Copy the requirements file into the container
+COPY ./requirements.txt /code/requirements.txt
+
+# Install dependencies from requirements.txt
+# --no-cache-dir ensures a smaller image size
+# --upgrade ensures we get the latest specified versions
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+# Copy all your application files (app.py, train.py, and your CSVs) into the container
+COPY . /code/
+
+# Tell the container to expose port 7860, which is the default for Gradio
+EXPOSE 7860
+
+# The command to run when the container starts.
+# This will launch your Gradio app.
+CMD ["python", "app.py"]