Instructions to use hf-tiny-model-private/tiny-random-SEWForCTC 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-SEWForCTC 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-SEWForCTC")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-SEWForCTC") model = AutoModelForCTC.from_pretrained("hf-tiny-model-private/tiny-random-SEWForCTC") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 458f33477daa7da16a8a90873d63f9f8ba117525a35735cf834450c39cf4af16
- Size of remote file:
- 225 kB
- SHA256:
- 8501990f77952f9d1f9108f97d902e792aa1671fb19edb00141ee92bc7fe3a89
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