Instructions to use BUT-FIT/DiCoW_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BUT-FIT/DiCoW_v2 with Transformers:
# Load model directly from transformers import AutoProcessor, WhisperForConditionalGenerationWithCTC processor = AutoProcessor.from_pretrained("BUT-FIT/DiCoW_v2") model = WhisperForConditionalGenerationWithCTC.from_pretrained("BUT-FIT/DiCoW_v2") - Notebooks
- Google Colab
- Kaggle
Update generation_config.json
Browse files- generation_config.json +1 -1
generation_config.json
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@@ -34,7 +34,7 @@
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],
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"bos_token_id": 50257,
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"ctc_margin": 0,
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-
"ctc_weight": 0.
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"decoder_start_token_id": 50258,
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"eos_token_id": 50257,
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"is_multilingual": true,
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],
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"bos_token_id": 50257,
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"ctc_margin": 0,
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+
"ctc_weight": 0.0,
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"decoder_start_token_id": 50258,
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"eos_token_id": 50257,
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"is_multilingual": true,
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