Instructions to use mohitsha/whisper-tiny-dynamic-quantized-onnxruntime with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mohitsha/whisper-tiny-dynamic-quantized-onnxruntime with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mohitsha/whisper-tiny-dynamic-quantized-onnxruntime")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("mohitsha/whisper-tiny-dynamic-quantized-onnxruntime") model = AutoModelForSpeechSeq2Seq.from_pretrained("mohitsha/whisper-tiny-dynamic-quantized-onnxruntime", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download decoder_model_quantized.onnx from mohitsha/whisper-tiny-dynamic-quantized-onnxruntime: direct link, hf CLI and curl.
- Browser
- Download file 50.4 MB
-
https://huggingface.co/mohitsha/whisper-tiny-dynamic-quantized-onnxruntime/resolve/main/decoder_model_quantized.onnx
- Command line
-
hf download hf://mohitsha/whisper-tiny-dynamic-quantized-onnxruntime/decoder_model_quantized.onnx
-
curl -L -o decoder_model_quantized.onnx https://huggingface.co/mohitsha/whisper-tiny-dynamic-quantized-onnxruntime/resolve/main/decoder_model_quantized.onnx
50.4 MB
- Xet hash:
- 949d6cafccaa9180394f9006eab2181be642ec3fbf5d8f772229d5b9b103dd14
- Size of remote file:
- 50.4 MB
- SHA256:
- 166803408e4c9c9ca7636f143ce1a72051c46a271f8baba501bc50e48bda62c3
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