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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44b307d86ca9c28242516667e8150ad4d30e650bfcb0cde642170d10ca9ea9c5
- Size of remote file:
- 143 kB
- SHA256:
- 2d7664d55a122f97578c93df5598a7916746c2e24441204dfac6d686431cda58
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