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@@ -70,20 +70,35 @@ In an experiment based on a [**blog post by Daniel Van Strien**](https://danielv
## Using ColPali with Qdrant
**Now it's time to try the code.** Here’s a simplified Notebook to test ColPali for yourself:
**Now it's time to try the code.** </br>
Here’s a simplified Notebook to test ColPali for yourself:
[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/sabrinaaquino/colpali-qdrant-demo/blob/main/colpali_demo_binary.ipynb)
Our goal is to go through a dataset of multilingual newspaper articles like the ones below. We will detect which images contain text about **UFO's** and **Top Secret** events.
![Qdrant and Colpali](/blog/qdrant-colpali/qdrant-colpali-4.png)
*The full dataset is accessible from the notebook.*
### Procedure
1. **Setup ColPali and Qdrant:** Import the necessary libraries, including a fine-tuned model optimized for your dataset (in this case, a UFO document set).
2. **Dataset Preparation:** Load your document images into ColPali, previewing complex images to appreciate the challenge for traditional retrieval methods.
3. **Qdrant Configuration:** Define your Qdrant collection, setting vector dimensions to 128. Enable Binary Quantization to optimize memory usage.
4. **Batch Uploading Vectors:** Use a retry checkpoint to handle any exceptions during indexing. Batch processing allows you to adjust batch size based on available GPU resources.
5. **Query Processing and Search:** Encode queries as multivectors for Qdrant. Set up rescoring and oversampling to fine-tune accuracy while optimizing speed.
### Results
> In our testing, the search time was reduced to 0.81 seconds.
This is significantly faster than with Scalar Quantization, and we still retrieved the top document matches with remarkable accuracy.
However, keep in mind that this is just a quick experiment. Performance may vary, so it's important to test Binary Quantization on your own datasets to see how it performs for your specific use case.
That said, it's promising to see Binary Quantization maintaining search quality while potentially offering performance improvements with ColPali.
## Future Directions with ColPali
![Qdrant and Colpali](/blog/qdrant-colpali/qdrant-colpali-2.png)