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🚀 New short course with Qdrant: Multi-vector Image Retrieval. Taught by Kacper Łukawski, Senior Developer Advocate at Qdrant, the course shows how multi-vector techniques outperform single-vector methods by matching text tokens to image patches directly. You’ll implement ColBERT to understand multi-vector search, apply ColPali for patch-level image retrieval, reduce memory with quantization and pooling, and use MUVERA to enable fast HNSW search. The course concludes with a full multi-modal RAG
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🚀 New short course with Qdrant: Multi-vector Image Retrieval. Taught by Kacper Łukawski, Senior Developer Advocate at Qdrant, the course shows how multi-vector techniques outperform single-vector methods by matching text tokens to image patches directly. You’ll implement ColBERT to understand multi-vector search, apply ColPali for patch-level image retrieval, reduce memory with quantization and pooling, and use MUVERA to enable fast HNSW search. The course concludes with a full multi-modal RAG
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What is the “Col” in ColBERT and ColPali? ⬇️Contextualized Late Interaction (Col) is used in models like ColBERT for text retrieval and ColPali for vision-based tasks, and it combines the high… | Victoria Slocum | 11 comments
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