Instructions to use mispeech/ced-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mispeech/ced-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="mispeech/ced-base", trust_remote_code=True)# Load model directly from transformers import AutoModelForAudioClassification model = AutoModelForAudioClassification.from_pretrained("mispeech/ced-base", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +4 -0
config.json
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"architectures": [
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"CedForAudioClassification"
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],
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"attn_drop_rate": 0.0,
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"center": true,
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"depth": 12,
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"architectures": [
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"CedForAudioClassification"
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],
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"auto_map": {
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"AutoModel": "modeling_ced.CedModel",
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"AutoModelForAudioClassification": "modeling_ced.CedForAudioClassification"
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},
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"attn_drop_rate": 0.0,
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"center": true,
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"depth": 12,
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