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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 65d513547e4481fbdbd5db8d379ff17fe5d992419b2540b06e986ba74e565fcd
- Size of remote file:
- 292 kB
- SHA256:
- 0671d62d8d4667d20dcf6ada222587ef323e9aa70a8754d37e52958c76976cf4
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