Instructions to use hf-internal-testing/tiny-random-WavLMForCTC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-WavLMForCTC 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-WavLMForCTC")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-WavLMForCTC") model = AutoModelForCTC.from_pretrained("hf-internal-testing/tiny-random-WavLMForCTC") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 19bc127e172b4dd804df87199a6cbe853bfc5faad3e9cccf3c3a8534e89f36d2
- Size of remote file:
- 123 kB
- SHA256:
- 40a0ba2bc24aafefa13b7edea8f4190e4ab3fd625983dde2c8556cf77b1aebf5
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