Instructions to use marma/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marma/test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="marma/test")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("marma/test") model = AutoModelForCTC.from_pretrained("marma/test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 374629809bdde2559b6b764c4d90c5bc77bdc50b675132bd2e84ef68e012e0c0
- Size of remote file:
- 1.26 GB
- SHA256:
- e77331afd00b912e7950d9f5dcd5b72e3cd0621b810d263234ccc29ad1252234
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