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justinchuby/onnx-genai-example-whisper-tiny
onnx-genai-example-whisper-tiny is a machine learning model from justinchuby. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Private real-weight ONNX package produced by Mobius from openai/whisper-tiny at immutable revision 169d4a4341b33bc18d8881c4b69c2e104e1cc0af. Source license: apache-2.0.
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From the Hugging Face model README
Private real-weight ONNX package produced by Mobius from
openai/whisper-tiny at immutable revision
169d4a4341b33bc18d8881c4b69c2e104e1cc0af. Source license: apache-2.0.
inference_metadata.yamlrequest.json and output.json real runtime evidencegraph_report.json, performance.json, source.json, and provenance.jsonObserved output: Mr. Quilter is the apostle of the middle classes and we are glad to welcome his gospel.
hf download justinchuby/onnx-genai-example-whisper-tiny --repo-type model --local-dir ./whisper-tiny
python - <<'PY'
from pathlib import Path
import onnxruntime as ort
root = Path("whisper-tiny")
for relative_path in ['decoder/model.onnx', 'encoder/model.onnx']:
session = ort.InferenceSession(
str(root / relative_path),
providers=['CPUExecutionProvider'],
)
print(relative_path, session.get_providers(), [x.name for x in session.get_inputs()])
PY
The exact successful probe request, output, versions, providers, and timings are
preserved in request.json, output.json, and performance.json.
Review inference_metadata.annotated.yaml for inline explanations of this package's workflow, tensor/state/cache contracts, and fail-closed omissions. inference_metadata.yaml remains the canonical machine-authored contract; automated validation confirms both files parse to the same metadata object.