vidore
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colpali-v1.3-hf

Visual Document Retrieval

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tonywu71 commited on Mar 8

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@@ -29,11 +29,7 @@ The HuggingFace `transformers` 🤗 implementation was contributed by Tony Wu ([
 ## Model Description
-This model is built iteratively starting from an off-the-shelf [SigLIP](https://huggingface.co/google/siglip-so400m-patch14-384) model.
-We finetuned it to create [BiSigLIP](https://huggingface.co/vidore/bisiglip) and fed the patch-embeddings output by SigLIP to an LLM, [PaliGemma-3B](https://huggingface.co/google/paligemma-3b-mix-448) to create [BiPali](https://huggingface.co/vidore/bipali).
-One benefit of inputting image patch embeddings through a language model is that they are natively mapped to a latent space similar to textual input (query).
-This enables leveraging the [ColBERT](https://arxiv.org/abs/2004.12832) strategy to compute interactions between text tokens and image patches, which enables a step-change improvement in performance compared to BiPali.
 ## Model Training

 ## Model Description
+Read the `transformers` 🤗 model card: https://huggingface.co/docs/transformers/en/model_doc/colpali.
 ## Model Training