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:
- 030cebc993c98894863f3c4849917c4e0dd3a0494cb8c6bc765fbb05575d5e54
- Size of remote file:
- 211 kB
- SHA256:
- 1fabdbe5ebe2d05dd0a682ce5664820e658837863ddc555a9a1601134247a814
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