Instructions to use oyemade/whisper-small-yo-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oyemade/whisper-small-yo-onnx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="oyemade/whisper-small-yo-onnx")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("oyemade/whisper-small-yo-onnx") model = AutoModelForSpeechSeq2Seq.from_pretrained("oyemade/whisper-small-yo-onnx", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download onnx/decoder_model_merged.onnx from oyemade/whisper-small-yo-onnx: direct link, hf CLI and curl.
- Browser
- Download file 615 MB
-
https://huggingface.co/oyemade/whisper-small-yo-onnx/resolve/main/onnx/decoder_model_merged.onnx
- Command line
-
hf download hf://oyemade/whisper-small-yo-onnx/onnx/decoder_model_merged.onnx
-
curl -L -o decoder_model_merged.onnx https://huggingface.co/oyemade/whisper-small-yo-onnx/resolve/main/onnx/decoder_model_merged.onnx
615 MB
- Xet hash:
- 59ab46b306e70976d08abceb1d12e70754ba42553d37def09d0fe79772a148d0
- Size of remote file:
- 615 MB
- SHA256:
- 7704a6a852de9981555226aa7a7b03c24b28f0fc4270f6a55439170f22d3aafc
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