Instructions to use hf-tiny-model-private/tiny-random-HubertForCTC 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-HubertForCTC 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-HubertForCTC")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-HubertForCTC") model = AutoModelForCTC.from_pretrained("hf-tiny-model-private/tiny-random-HubertForCTC") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 586cdc874297fb396f67d4e9e4ecebde2752a6e792e199a83209edb29cd79c28
- Size of remote file:
- 118 kB
- SHA256:
- 010fbed650be4fd5b7abd1359f2cfc3ecb925c23b406ba2bd4f7b0c53838f7ed
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