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# CUDA 12.1 (works best with PyTorch cu121 wheels on T4) + Ubuntu 22.04
FROM nvidia/cuda:12.1.1-cudnn8-runtime-ubuntu22.04
# ---- Basics & paths ---------------------------------------------------------
ENV DEBIAN_FRONTEND=noninteractive
WORKDIR /home/user/app
# Runtime/env hygiene + stable caches/dirs
ENV OMP_NUM_THREADS=1 \
TOKENIZERS_PARALLELISM=false \
PYTHONUNBUFFERED=1 \
HF_HOME=/home/user/.cache/huggingface \
TRANSFORMERS_CACHE=/home/user/.cache/huggingface/transformers \
HF_DATASETS_CACHE=/home/user/.cache/huggingface/datasets \
OFFLOAD_DIR=/home/user/app/offload \
MERGED_MODEL_DIR=/home/user/app/merged-model \
QUANTIZE=4bit
# (Optional) helps some CUDA containers/tools detect GPU features
ENV NVIDIA_VISIBLE_DEVICES=all \
NVIDIA_DRIVER_CAPABILITIES=compute,utility
# ---- System deps ------------------------------------------------------------
RUN apt-get update && apt-get install -y --no-install-recommends \
python3 python3-pip git git-lfs ca-certificates && \
rm -rf /var/lib/apt/lists/* && \
git lfs install
# ---- Python deps ------------------------------------------------------------
# 1) Upgrade pip
RUN python3 -m pip install --upgrade pip
# 2) GPU-enabled PyTorch for CUDA 12.1 (good match for T4)
RUN python3 -m pip install --no-cache-dir \
--index-url https://download.pytorch.org/whl/cu121 \
torch==2.4.0 torchvision==0.19.0 torchaudio==2.4.0
# 3) Project requirements (should include bitsandbytes etc.)
COPY requirements.txt .
RUN python3 -m pip install --no-cache-dir -r requirements.txt
# ---- App code ---------------------------------------------------------------
COPY . .
RUN mkdir -p "$OFFLOAD_DIR" "$MERGED_MODEL_DIR" "$HF_HOME" "$TRANSFORMERS_CACHE"
# ---- Networking -------------------------------------------------------------
EXPOSE 7860
# ---- Entrypoint -------------------------------------------------------------
CMD ["python3", "app.py"]
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