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_static_scatter.onnx from mohitsha/whisper-tiny-static-shape-quantized-SL-448: direct link, hf CLI and curl.
- Browser
- Download file 94 MB
-
https://huggingface.co/mohitsha/whisper-tiny-static-shape-quantized-SL-448/resolve/main/decoder_model_quantized_static_scatter.onnx
- Command line
-
hf download hf://mohitsha/whisper-tiny-static-shape-quantized-SL-448/decoder_model_quantized_static_scatter.onnx
-
curl -L -o decoder_model_quantized_static_scatter.onnx https://huggingface.co/mohitsha/whisper-tiny-static-shape-quantized-SL-448/resolve/main/decoder_model_quantized_static_scatter.onnx
94 MB
- Xet hash:
- 30c4912629c76f8ebe592fed9688a1be54fe0bfed6c69bca404e97cdc8a83e78
- Size of remote file:
- 94 MB
- SHA256:
- beb38ca649c013239e673b86fa9630bd508bbb22ea30af9929b05cd4007bcff0
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