Instructions to use Ravshan/pytorch_model.bin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ravshan/pytorch_model.bin with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Ravshan/pytorch_model.bin")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Ravshan/pytorch_model.bin") model = AutoModelForCTC.from_pretrained("Ravshan/pytorch_model.bin") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a7b8d79c19dcdc59902d7c15b3644e20d350717775c2210d64c5d527c2938f4
- Size of remote file:
- 5.05 kB
- SHA256:
- 9a602ed440221c0d532e3e409082922aa044a9f037299e00866db3a19f4ca244
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