Instructions to use mohitsha/whisper-tiny-smooth-quant with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mohitsha/whisper-tiny-smooth-quant with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mohitsha/whisper-tiny-smooth-quant")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("mohitsha/whisper-tiny-smooth-quant") model = AutoModelForSpeechSeq2Seq.from_pretrained("mohitsha/whisper-tiny-smooth-quant") - Notebooks
- Google Colab
- Kaggle
Upload config.json with huggingface_hub
Browse files- config.json +1 -1
config.json
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{
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"_name_or_path": "
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"activation_dropout": 0.0,
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"activation_function": "gelu",
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"apply_spec_augment": false,
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"_name_or_path": "output_whisper_smooth_quant_23/config.json",
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"activation_dropout": 0.0,
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"activation_function": "gelu",
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"apply_spec_augment": false,
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