Instructions to use Aniemore/wav2vec2-emotion-russian-resd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aniemore/wav2vec2-emotion-russian-resd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Aniemore/wav2vec2-emotion-russian-resd")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Aniemore/wav2vec2-emotion-russian-resd") model = AutoModelForAudioClassification.from_pretrained("Aniemore/wav2vec2-emotion-russian-resd") - Notebooks
- Google Colab
- Kaggle
Upload feature extractor
Browse files- preprocessor_config.json +1 -1
preprocessor_config.json
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"feature_size": 1,
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"padding_side": "right",
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"padding_value": 0.0,
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"processor_class": "
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"return_attention_mask": true,
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"sampling_rate": 16000
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}
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"feature_size": 1,
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"padding_side": "right",
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"padding_value": 0.0,
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"processor_class": "Wav2Vec2ProcessorWithLM",
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"return_attention_mask": true,
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"sampling_rate": 16000
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}
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