llama32-3b-instruct / Dockerfile
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FROM nvidia/cuda:11.7.1-cudnn8-runtime-ubuntu22.04
ENV VLLM_LOGGING_LEVEL=DEBUG
ENV HF_HOME=/tmp/.cache/huggingface
ENV OMP_NUM_THREADS=1
# https://github.com/vllm-project/vllm/blob/v0.10.0/docs/getting_started/installation/gpu/rocm.inc.md?plain=1#L124
ENV VLLM_USE_TRITON_FLASH_ATTN=0
# https://github.com/vllm-project/vllm/blob/v0.10.0/docs/getting_started/quickstart.md?plain=1#L213
# `FLASH_ATTN` or `FLASHINFER` or `XFORMERS`.
# https://github.com/vllm-project/vllm/blob/main/vllm/envs.py#L426-L435
# Backend for attention computation
# Available options:
# - "TORCH_SDPA": use torch.nn.MultiheadAttention
# - "FLASH_ATTN": use FlashAttention
# - "XFORMERS": use XFormers
# - "ROCM_FLASH": use ROCmFlashAttention
# - "FLASHINFER": use flashinfer
# - "FLASHMLA": use FlashMLA
# Choose XFORMERS that most stable for T4
ENV VLLM_ATTENTION_BACKEND=XFORMERS
RUN apt-get update && apt-get install -y python3 python3-pip git
RUN pip3 install --upgrade pip
# Install vLLM
RUN pip3 install vllm==0.10.0 --extra-index-url https://download.pytorch.org/whl/cu113
RUN useradd -m appuser
USER appuser
RUN mkdir -p /tmp/.cache/huggingface
# Download at build time,
# to ensure during restart we won't have to wait for the download from HF (only wait for docker pull).
# In Docker Spaces, the secrets management is different for security reasons.
# Once you create a secret in the Settings tab,
# you can expose the secret by adding the following line in your Dockerfile:
#
# For example, if SECRET_EXAMPLE is the name of the secret you created in the Settings tab,
# you can read it at build time by mounting it to a file, then reading it with $(cat /run/secrets/SECRET_EXAMPLE).
# https://huggingface.co/docs/hub/en/spaces-sdks-docker#buildtime
#
# AFTER TRIAL AND ERROR WE GOT 16GB (16431849854 bytes) OF LAYERS :(
#
# RUN --mount=type=secret,id=HF_TOKEN,mode=0444,required=true HF_TOKEN=$(cat /run/secrets/HF_TOKEN) python /app/download_model.py
EXPOSE 7860
# Export for runtime environment
CMD vllm serve \
--model "meta-llama/Llama-3.2-3B-Instruct" \
--task generate \
--revision "0cb88a4f764b7a12671c53f0838cd831a0843b95" \
--code-revision "0cb88a4f764b7a12671c53f0838cd831a0843b95" \
--tokenizer-revision "0cb88a4f764b7a12671c53f0838cd831a0843b95" \
--seed 42 \
--host 0.0.0.0 \
--port 7860 \
--max-num-batched-tokens 32768 \
--max-model-len 32768 \
--dtype float16 \
--enforce-eager \
--gpu-memory-utilization 0.9 \
--enable-prefix-caching \
--disable-log-requests \
--trust-remote-code