Instructions to use hf-internal-testing/tiny-random-DacModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DacModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-DacModel")# Load model directly from transformers import AutoFeatureExtractor, AutoModel extractor = AutoFeatureExtractor.from_pretrained("hf-internal-testing/tiny-random-DacModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-DacModel") - Notebooks
- Google Colab
- Kaggle
Upload feature extractor
Browse files- preprocessor_config.json +9 -0
preprocessor_config.json
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{
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"feature_extractor_type": "DacFeatureExtractor",
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"feature_size": 1,
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"hop_length": 512,
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"padding_side": "right",
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"padding_value": 0.0,
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"return_attention_mask": true,
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"sampling_rate": 16000
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}
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