What is a model signature and why does it matter?
mediumAnswer
- Explicit schema of model inputs + outputs: field names, types, shapes.
- Enables: (1) validation at serve time (reject invalid inputs).
- (2) auto-generated API + docs.
- (3) preventing training-serving skew (compare training schema to serve schema).
- (4) type-safe deployment.
- Standards: MLflow ModelSignature, ONNX metadata, OpenAI schema.
- Include example inputs + outputs.
- Version signature with model.
Check yourself — multiple choice
- Random
- Explicit schema of inputs + outputs (names/types/shapes); enables input validation + auto-doc + skew detection + type-safe deploy; MLflow ModelSignature / ONNX metadata
- Just weights
- Not real
Model signature: input/output schema; validate + doc + skew + type-safe.
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