Instructions to use UCSC-VLAA/openvision-vit-small-patch8-160 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UCSC-VLAA/openvision-vit-small-patch8-160 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="UCSC-VLAA/openvision-vit-small-patch8-160")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("UCSC-VLAA/openvision-vit-small-patch8-160", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add model card
#1
by nielsr HF Staff - opened
This PR adds a model card for the OpenVision model, linking it to the paper OpenVision: A Fully-Open, Cost-Effective Family of Advanced Vision Encoders for Multimodal Learning.
It also adds a relevant pipeline tag, library name and license.
Xianhang changed pull request status to merged