Zero-Shot Image Classification
Transformers
Safetensors
tipsv2
feature-extraction
vision
image-text
contrastive-learning
zero-shot
custom_code
Instructions to use google/tipsv2-g14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/tipsv2-g14 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="google/tipsv2-g14", trust_remote_code=True) pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("google/tipsv2-g14", trust_remote_code=True) model = AutoModel.from_pretrained("google/tipsv2-g14", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add arXiv paper link to citation
Browse files
README.md
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title = {{TIPSv2: Advancing Vision-Language Pretraining with Enhanced Patch-Text Alignment}},
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author = {Cao, Bingyi and Chen, Koert and Maninis, Kevis-Kokitsi and Chen, Kaifeng and Karpur, Arjun and Xia, Ye and Dua, Sahil and Dabral, Tanmaya and Han, Guangxing and Han, Bohyung and Ainslie, Joshua and Bewley, Alex and Jacob, Mithun and Wagner, Rene and Ramos, Washington and Choromanski, Krzysztof and Seyedhosseini, Mojtaba and Zhou, Howard and Araujo, Andre},
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booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
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year = {2026}
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}
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```
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title = {{TIPSv2: Advancing Vision-Language Pretraining with Enhanced Patch-Text Alignment}},
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author = {Cao, Bingyi and Chen, Koert and Maninis, Kevis-Kokitsi and Chen, Kaifeng and Karpur, Arjun and Xia, Ye and Dua, Sahil and Dabral, Tanmaya and Han, Guangxing and Han, Bohyung and Ainslie, Joshua and Bewley, Alex and Jacob, Mithun and Wagner, Rene and Ramos, Washington and Choromanski, Krzysztof and Seyedhosseini, Mojtaba and Zhou, Howard and Araujo, Andre},
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booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
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year = {2026},
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url = {https://arxiv.org/abs/2604.12012}
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}
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```
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