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clip-vit-gigantic-patch14-laion2b
cs-giung/clip-vit-gigantic-patch14-laion2b
clip-vit-gigantic-patch14-laion2b is a zero-shot image classification model from cs-giung. Use it for the zero-shot image classification task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
Contrastive Language-Image Pretraining (CLIP) model pre-trained on LAION-2B at resolution 224x224. It was introduced in the paper Learning Transferable Visual Models From Natural Language Supervision and further repro…
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Model card
From the Hugging Face model README
CLIP
Contrastive Language-Image Pretraining (CLIP) model pre-trained on LAION-2B at resolution 224x224. It was introduced in the paper Learning Transferable Visual Models From Natural Language Supervision and further reproduced in the follow-up paper Reproducible scaling laws for contrastive language-image learning.
The weights were converted from the laion/CLIP-ViT-bigG-14-laion2B-39B-b160k presented in the OpenCLIP LAION-2B collections.
- Task
- Zero-Shot Image Classification
- Library
- transformers
- Type
- clip
- License
- mit
- Created
- Jul 3, 2024
- Updated
- Jul 3, 2024