The CLIP model maps text and images to a shared vector space, enabling various applications such as image search, zero-shot image classification, and image clustering. The model can be used easily after installation, and its performance is demonstrated through zero-shot ImageNet validation set accuracy scores. Multilingual versions of the model are also available for 50+ languages.
https://api.deepinfra.com/v1/openai/v1/embeddings| Model | Context | Max out |
|---|---|---|
| all-MiniLM-L12-v2 | — | — |
| all-MiniLM-L6-v2 | — | — |
| all-mpnet-base-v2 | — | — |
| clip-ViT-B-32-multilingual-v1 | — | — |
| clip-ViT-B-32 | — | — |
| multi-qa-mpnet-base-dot-v1 | — | — |
| paraphrase-MiniLM-L6-v2 | — | — |
/v1/models/deepinfra/sentence-transformers/clip-ViT-B-32The CLIP model maps text and images to a shared vector space, enabling various applications such as image search, zero-shot image classification, and image clustering. The model can be used easily after installation, and its performance is demonstrated through zero-shot ImageNet validation set accuracy scores. Multilingual versions of the model are also available for 50+ languages.