Instructions to use hf-tiny-model-private/tiny-random-HubertModel 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-HubertModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-HubertModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-HubertModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-HubertModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 926bb5e9dba9a87ab00e7f505ccceacf988e4a29f28c45a4b0aa2486c3ba8bd5
- Size of remote file:
- 132 kB
- SHA256:
- c2d61423537e9afe1ac4374176d484f14aedd0954bc7f4dcb27e795f8bc291ea
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