Instructions to use hf-internal-testing/tiny-random-HubertModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-HubertModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-HubertModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-HubertModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-HubertModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 106ca6a39a7657b8f9d9b4b3028cb16b6a971e296643bfd25335f687c02d75c8
- Size of remote file:
- 211 kB
- SHA256:
- 217ec25179687c0b3dc4d6df9bcd67c565266700746cd1afaf67d54b5acda30e
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