Instructions to use cwkeam/mctc-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cwkeam/mctc-large with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import MCTCForCTC model = MCTCForCTC.from_pretrained("cwkeam/mctc-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 497 Bytes
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"K": 257,
"do_normalize": true,
"feature_extractor_type": "MCTCFeatureExtractor",
"feature_size": 80,
"frame_signal_scale": 32768.0,
"hop_length": 10,
"mel_floor": 1.0,
"n_fft": 512,
"normalize_means": true,
"normalize_vars": true,
"padding_side": "right",
"padding_value": 0.0,
"preemphasis_coeff": 0.97,
"return_attention_mask": false,
"sample_size": 400,
"sample_stride": 160,
"sampling_rate": 16000,
"win_function": "hamming_window",
"win_length": 25
}
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