Create Dockerfile

Dockerfile

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+# Use a high-performance CUDA base image
+FROM nvidia/cuda:12.1.0-devel-ubuntu22.04
+
+# Set environment variables for non-interactive installs
+ENV DEBIAN_FRONTEND=noninteractive
+ENV PYTHONUNBUFFERED=1
+
+# Install Python and essential build tools
+RUN apt-get update && apt-get install -y \
+    python3-pip \
+    python3-dev \
+    git \
+    && rm -rf /var/lib/apt/lists/*
+
+# Upgrade pip and install wheel
+RUN pip3 install --no-cache-dir --upgrade pip wheel
+
+# Install Unsloth and its core dependencies
+# We use the specific install command recommended for CUDA 12.1
+RUN pip3 install --no-cache-dir \
+    "unsloth[colab-new] @ git+https://github.com" \
+    --extra-index-url https://download.pytorch.org
+
+# Install TRL and Transformers for the Trainer subclassing
+RUN pip3 install --no-cache-dir trl transformers accelerate datasets
+
+# Set the working directory
+WORKDIR /app
+
+# Copy your custom logic into the container
+COPY . /app
+
+# The entrypoint to start training
+CMD ["python3", "train.py"]