Instructions to use UCSC-VLAA/openvision-vit-large-patch14-336 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UCSC-VLAA/openvision-vit-large-patch14-336 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="UCSC-VLAA/openvision-vit-large-patch14-336")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("UCSC-VLAA/openvision-vit-large-patch14-336", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from UCSC-VLAA/openvision-vit-large-patch14-336: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
-
https://huggingface.co/UCSC-VLAA/openvision-vit-large-patch14-336/resolve/main/tokenizer.json
- Command line
-
hf download hf://UCSC-VLAA/openvision-vit-large-patch14-336/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/UCSC-VLAA/openvision-vit-large-patch14-336/resolve/main/tokenizer.json
711 kB
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