Instructions to use enrybds/firstmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use enrybds/firstmodel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="enrybds/firstmodel")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("enrybds/firstmodel") model = AutoModelForCTC.from_pretrained("enrybds/firstmodel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eba70cde76cb6948d6a505a928b5e114e7d795bb8da15f4b8e7ad7260d4980a8
- Size of remote file:
- 1.26 GB
- SHA256:
- 722f16789b131743a4281c2e76c9a6e9fe64de9cd30d7cd561afe67928ec586e
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