Instructions to use microsoft/wavlm-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/wavlm-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="microsoft/wavlm-base")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("microsoft/wavlm-base") model = AutoModel.from_pretrained("microsoft/wavlm-base") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 1c44dff
Update config.json
Browse files- config.json +2 -1
config.json
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"torch_dtype": "float32",
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"transformers_version": "4.14.0.dev0",
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"use_weighted_layer_sum": false,
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"vocab_size": 32
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}
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"torch_dtype": "float32",
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"transformers_version": "4.14.0.dev0",
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"use_weighted_layer_sum": false,
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"vocab_size": 32,
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"tokenizer_class": "Wav2Vec2CTCTokenizer"
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}
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