Instructions to use hf-internal-testing/tiny-random-Data2VecAudioForCTC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Data2VecAudioForCTC 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-Data2VecAudioForCTC")# Load model directly from transformers import AutoTokenizer, AutoModelForCTC tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-Data2VecAudioForCTC") model = AutoModelForCTC.from_pretrained("hf-internal-testing/tiny-random-Data2VecAudioForCTC") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c2918cb85d3427809251398d127b2b3d14650458bd4b1188d5e5d8d8f8f1e36
- Size of remote file:
- 296 kB
- SHA256:
- 050fa28f4c94b9c5c5b938f35a363eda33112b0521c4578637ac5314d6750d7b
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