Instructions to use 7ocho/WMAC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 7ocho/WMAC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="7ocho/WMAC")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("7ocho/WMAC") model = AutoModelForSpeechSeq2Seq.from_pretrained("7ocho/WMAC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update generation_config.json
Browse files- generation_config.json +1 -1
generation_config.json
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"forced_decoder_ids": null,
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"language": null,
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"length_penalty": 1.0,
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"max_length":
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"min_length": 0,
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"no_repeat_ngram_size": 4,
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"num_assistant_tokens": 20,
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"forced_decoder_ids": null,
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"language": null,
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"length_penalty": 1.0,
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"max_length": 444,
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"min_length": 0,
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"no_repeat_ngram_size": 4,
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"num_assistant_tokens": 20,
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