Instructions to use hf-tiny-model-private/tiny-random-ViltModel 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-ViltModel 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-ViltModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-ViltModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-ViltModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df76090a0f35c74d741e05a081327b47ebd1ee64b4792ee35a97499b1460c7d2
- Size of remote file:
- 397 kB
- SHA256:
- 81a751609ff14868a1fd9850bc35538987dd29aa9943043b2cfa49aad8c9706d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.