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To generate the embeddings use ```google/siglip2-so400m-patch16-512``` with no fine tuning.
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You have a tiny script in generate_embeddings.py to generate a pickle file with the embeddings, provided a Pandas DataFrame ```tasks_df``` with a col ```"image_path"``` that contains all the images paths.
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To generate the embeddings use ```google/siglip2-so400m-patch16-512``` with no fine tuning.
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You have a tiny script in generate_embeddings.py to generate a pickle file with the embeddings, provided a Pandas DataFrame ```tasks_df``` with a col ```"image_path"``` that contains all the images paths.
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Then you can use the resulting embeddings with the model here uploaded.
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