jinaai
/

jina-clip-v1

Feature Extraction

Transformers.js

sentence-similarity

🇪🇺 Region: EU

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hanxiao commited on May 31

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a3213ad

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@@ -43,7 +43,7 @@ model = AutoModel.from_pretrained('jinaai/jina-clip-v1', trust_remote_code=True)
 sentences = ['The Eiffel Tower is in Paris.', 'The capital of France is Paris.']
 images = ['tower.jpg', 'paris.jpg']  # here we use filenames, but it also accepts URL, PIL.Image objects and dataURI strings
-text_embeddings = model.encode_text(sentences)
 image_embeddings = model.encode_image(images)
 print(cos_sim(text_embeddings[0], text_embeddings[1])) # text embedding similarity

 sentences = ['The Eiffel Tower is in Paris.', 'The capital of France is Paris.']
 images = ['tower.jpg', 'paris.jpg']  # here we use filenames, but it also accepts URL, PIL.Image objects and dataURI strings
+text_embeddings = model.encode_text(sentences)  # encode_text and encode_image are helper function made by us to easily get embeddings
 image_embeddings = model.encode_image(images)
 print(cos_sim(text_embeddings[0], text_embeddings[1])) # text embedding similarity