Instructions to use hf-internal-testing/tiny-random-UniSpeechForCTC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-UniSpeechForCTC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hf-internal-testing/tiny-random-UniSpeechForCTC")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-UniSpeechForCTC") model = AutoModelForCTC.from_pretrained("hf-internal-testing/tiny-random-UniSpeechForCTC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b39942d9b4e4c1a088d0c1f92f590f7d547c2b815c31a8365a368881942ec171
- Size of remote file:
- 135 kB
- SHA256:
- 4778381e8371957bfaa8f8f4ee717a5674e73aa782915422035eff802a26eab8
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