Instructions to use mohitsha/whisper-tiny-static-shape-quantized-SL-448 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mohitsha/whisper-tiny-static-shape-quantized-SL-448 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mohitsha/whisper-tiny-static-shape-quantized-SL-448")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("mohitsha/whisper-tiny-static-shape-quantized-SL-448") model = AutoModelForSpeechSeq2Seq.from_pretrained("mohitsha/whisper-tiny-static-shape-quantized-SL-448", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download decoder_model_quantized.onnx from mohitsha/whisper-tiny-static-shape-quantized-SL-448: direct link, hf CLI and curl.
- Browser
- Download file 174 MB
-
https://huggingface.co/mohitsha/whisper-tiny-static-shape-quantized-SL-448/resolve/main/decoder_model_quantized.onnx
- Command line
-
hf download hf://mohitsha/whisper-tiny-static-shape-quantized-SL-448/decoder_model_quantized.onnx
-
curl -L -o decoder_model_quantized.onnx https://huggingface.co/mohitsha/whisper-tiny-static-shape-quantized-SL-448/resolve/main/decoder_model_quantized.onnx
174 MB
- Xet hash:
- 577829e6e3341e44ae22669672a2ab1002ea4e2250853ae5dbbfd112530b0fc2
- Size of remote file:
- 174 MB
- SHA256:
- d146c680a82b0e85900a2b5782af1fc3be9df67d8a89ac7a6636e7f36fa6b22c
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