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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 21ff3a7d81e3c6c45ee981d3226bdc866685006035f3dfd25f457fbbfdd0b1bc
- Size of remote file:
- 115 kB
- SHA256:
- bdcdfbd5a32665553ee7e21f8b0b1b21331ef12084649f30831faf292cc55cec
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.