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AI model persistence
When containerizing AI applications, ensure proper model persistence by mounting volumes to the default cache locations used by AI frameworks and setting appropriate environment variables. This prevents redundant downloads of large models and improves development efficiency.
When containerizing AI applications, ensure proper model persistence by mounting volumes to the default cache locations used by AI frameworks and setting appropriate environment variables. This prevents redundant downloads of large models and improves development efficiency.
Example for Hugging Face models in Docker:
volumes:
- models:/root/.cache/huggingface
environment:
HF_HOME: /root/.cache/huggingface