Instructions to use hf-tiny-model-private/tiny-random-UniSpeechSatForCTC 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-UniSpeechSatForCTC 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-UniSpeechSatForCTC")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-UniSpeechSatForCTC") model = AutoModelForCTC.from_pretrained("hf-tiny-model-private/tiny-random-UniSpeechSatForCTC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4954da59401a067a4caf018153e482b4d5349ff86d32c57f2290d90196e2ae8c
- Size of remote file:
- 136 kB
- SHA256:
- 01746de730075c1cab2b07783f1d5d0adf7e1c0b1b7456c4300c240fd7e3eac1
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