You baked the model into the image. One env var can silently un-bake it
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On serverless GPU, cold start is image pull plus model load. The single biggest win is usually to stop downloading weights at boot: download them at build time so they ship inside the image and load from local disk instead. The setup is two lines. Point the cache at a path inside the image, then fetch during the build: ENV HF_HOME=/opt/huggingface RUN python -c "from huggingface_hub import snapshot_download; snapshot_download(' ', revision=' ')" snapshot_download writes into HF_HOME , that…
1Key Takeaways
- On serverless GPU, cold start is image pull plus model load.
- The single biggest win is usually to stop downloading weights at boot: download them at build time so they ship inside the image and load from local disk instead.
- Point the cache at a path inside the image, then fetch during the build: ENV HF_HOME=/opt/huggingface RUN python -c "from huggingface_hub import snapshot_download; snapshot_download(' ', revision=' ')" snapshot_download writes into HF_HOME , that….
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that on serverless GPU, cold start is image pull plus model load.
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