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scores = processor.score_retrieval(query_embeddings.embeddings, image_embeddings.embeddings)
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## Limitations
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- **Focus**: The model primarily focuses on PDF-type documents and high-ressources languages, potentially limiting its generalization to other document types or less represented languages.
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scores = processor.score_retrieval(query_embeddings.embeddings, image_embeddings.embeddings)
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```
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## Resources
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- The *ColPali* arXiv paper can be found [here](https://doi.org/10.48550/arXiv.2407.01449). π
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- The official blog post detailing ColPali can be found [here](https://huggingface.co/blog/manu/colpali). π
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- The original model implementation code for the ColPali model and for the `colpali-engine` package can be found [here](https://github.com/illuin-tech/colpali). π
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- Cookbooks for learning to use the transformers-native version of *ColPali*, fine-tuning, and similarity maps generation can be found [here](https://github.com/tonywu71/colpali-cookbooks). π
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## Limitations
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- **Focus**: The model primarily focuses on PDF-type documents and high-ressources languages, potentially limiting its generalization to other document types or less represented languages.
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