Instructions to use hf-tiny-model-private/tiny-random-UniSpeechForCTC 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-UniSpeechForCTC 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-UniSpeechForCTC")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-UniSpeechForCTC") model = AutoModelForCTC.from_pretrained("hf-tiny-model-private/tiny-random-UniSpeechForCTC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0be564146f34a4b400dd45b4d8579ed0c9ddf75a8d17777679406c89fdf8a35
- Size of remote file:
- 135 kB
- SHA256:
- 017ae49fb7583071314682c9e9ee0a1224ee8daf996d771218719b3932abe72d
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