Instructions to use mispeech/dasheng-0.6B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mispeech/dasheng-0.6B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="mispeech/dasheng-0.6B", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mispeech/dasheng-0.6B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
11 days ago
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Fix batched inputs longer than target_length (clips mixed) and keep the last full segment (#2)
- Fix batched inputs longer than target_length (clips mixed) and keep the last full segment (60da524a56a08874c81a260af00eda9324ab6e36) Co-authored-by: Wataru-Nakata <Wataru@users.noreply.huggingface.co>ac03390
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Fix `Tensor.item() cannot be called on meta tensors` error during loading with transformers>=5 (#1)
- Fix `Tensor.item() cannot be called on meta tensors` error during loading with transformers>=5 (1412eb9e655ead9d315610e404550a31207d7c33) Co-authored-by: zhoukz <zhoukz@users.noreply.huggingface.co>9ea8bcc
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