Instructions to use mispeech/dasheng-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mispeech/dasheng-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="mispeech/dasheng-base", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mispeech/dasheng-base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 14fbdefdd30b56cec22741af237541fb692b0b799a35aaee777b0133649ad59f
- Size of remote file:
- 342 MB
- SHA256:
- adaa439ebec13933501242364a29b7912c2695d0354061b278c873438b2736c3
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