Instructions to use hf-tiny-model-private/tiny-random-SEWDForCTC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-SEWDForCTC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hf-tiny-model-private/tiny-random-SEWDForCTC")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-SEWDForCTC") model = AutoModelForCTC.from_pretrained("hf-tiny-model-private/tiny-random-SEWDForCTC") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a23ba559c9a1c49f7498d8c5fa9cd735faf46563e18b71fdb4e7870f7f19d486
- Size of remote file:
- 275 kB
- SHA256:
- 4069b732571b34065bf129030cd37928493a64a5c9d0d19d101b270ad9b1a833
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