This is an open-weight CLIP model variant trained by LAION on the LAION-2B dataset. It maps images and text into a shared embedding space for tasks such as zero-shot image classification, image-text retrieval, and multimodal similarity scoring. The model is distributed on Hugging Face and can be used with the OpenCLIP or transformers libraries.
In the Multimodal & vision space, CLIP ViT L 14 laion2B s32B b82K takes a focused approach. It focuses on finding and using high-quality open weights for contrastive image-text representation learning. It is built as an open-source project for machine learning researchers and developers. CLIP ViT L 14 laion2B s32B b82K is open source under the Open Source license. CLIP ViT L 14 laion2B s32B b82K is available on the web and API.
It is developed by LAION, and it first shipped in 2021. The project is developed in the open on GitHub with 14k stars and 115 commits in the last 90 days. Key capabilities include Image-Text Similarity, Zero-Shot Classification, and OpenCLIP Compatible.
Summary written by a language model from the project’s public pages.
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