Instructions to use kmrabby/crisp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kmrabby/crisp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="kmrabby/crisp")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("kmrabby/crisp") model = AutoModelForSpeechSeq2Seq.from_pretrained("kmrabby/crisp") - Notebooks
- Google Colab
- Kaggle
fix
Browse files- generation_config.json +1 -0
generation_config.json
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"pad_token_id": 50257,
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"prev_sot_token_id": 50362,
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"return_timestamps": true,
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"suppress_tokens": [
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1, 2, 7, 8, 9, 10, 14, 25, 26, 27, 28, 29, 31, 58, 59, 60, 61, 62, 63, 90,
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91, 92, 93, 256, 257, 261, 262, 269, 272, 274, 275, 276, 277, 280, 283, 286,
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"pad_token_id": 50257,
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"prev_sot_token_id": 50362,
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"return_timestamps": true,
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"return_token_timestamps": true,
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"suppress_tokens": [
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1, 2, 7, 8, 9, 10, 14, 25, 26, 27, 28, 29, 31, 58, 59, 60, 61, 62, 63, 90,
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91, 92, 93, 256, 257, 261, 262, 269, 272, 274, 275, 276, 277, 280, 283, 286,
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