Instructions to use brever/dummy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use brever/dummy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="brever/dummy")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("brever/dummy") model = AutoModelForCTC.from_pretrained("brever/dummy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b74feed4205521133b8a857924c880efba2a24b3c70510ddab3a12a97e747dfd
- Size of remote file:
- 378 MB
- SHA256:
- 4a2ec00bc9f8c0cf8a851f12df9e3c2c84b7d641327637d44ae60b7fad914f3b
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