Instructions to use TSunm/Vintern-3B-R-beta-ViVQA-X with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TSunm/Vintern-3B-R-beta-ViVQA-X with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TSunm/Vintern-3B-R-beta-ViVQA-X", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c423dbe9f9571b9d1fa775193c9c22b4ebd2737b9b42bb112fc190dc1fbcecb
- Size of remote file:
- 11.4 MB
- SHA256:
- f167a8394b8900bf9d8249a47d4d29e1c0242f557f27f602d8d7f66b7a4e9234
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