Instructions to use yxdu/ESRT-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yxdu/ESRT-4B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="yxdu/ESRT-4B", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("yxdu/ESRT-4B", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a3e0095767e66f8f17c50ffc107b015a7a84503e91e678efd07334941e23dc12
- Size of remote file:
- 33.4 MB
- SHA256:
- d9a0be69780559df037b0e7118dcfdde29dd75d01a67cc999ef0dc0db5cb1725
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