Instructions to use mispeech/ced-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mispeech/ced-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="mispeech/ced-small", trust_remote_code=True)# Load model directly from transformers import AutoModelForAudioClassification model = AutoModelForAudioClassification.from_pretrained("mispeech/ced-small", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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```python
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>>> from optimum.onnxruntime import ORTModelForAudioClassification
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>>> model_name = "mispeech/ced-
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>>> model = ORTModelForAudioClassification.from_pretrained(model_name, trust_remote_code=True)
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>>> import torchaudio
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```python
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>>> from optimum.onnxruntime import ORTModelForAudioClassification
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>>> model_name = "mispeech/ced-small"
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>>> model = ORTModelForAudioClassification.from_pretrained(model_name, trust_remote_code=True)
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>>> import torchaudio
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