Instructions to use Rahul3215/swecha-gonthuka-asr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rahul3215/swecha-gonthuka-asr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Rahul3215/swecha-gonthuka-asr")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Rahul3215/swecha-gonthuka-asr") model = AutoModelForCTC.from_pretrained("Rahul3215/swecha-gonthuka-asr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 298 Bytes
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"feature_extractor": {
"do_normalize": true,
"feature_extractor_type": "Wav2Vec2FeatureExtractor",
"feature_size": 1,
"padding_side": "right",
"padding_value": 0,
"return_attention_mask": false,
"sampling_rate": 16000
},
"processor_class": "Wav2Vec2Processor"
}
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