The code used to train and run inference with the ColVision models, e.g. ColPali, ColQwen2, and ColSmol.
-
Updated
Sep 7, 2026 - Python
The code used to train and run inference with the ColVision models, e.g. ColPali, ColQwen2, and ColSmol.
The repo provides the code for Qdrant for efficient image indexing and retrieval using models such as ColPali, ColQwen, and VDR-2B-Multi-V1, jina embeddings v4 etc enhancing multimodal search capabilities across various applications.
Search your Mac by what a page looks like. ColQwen2 over page images, everything local.
Vision-first document RAG for PDF, DOCX, and image QA/extraction with ColQwen2, Qwen2.5-VL, Qdrant, and FastAPI.
Python library for MUVERA multi-vector retrieval via Fixed Dimensional Encodings. ColBERT / ColQwen2 / ColQwen3.5 compatible.
Multimodal RAG that retrieves document pages as images using ColQwen2 late-interaction search, fused with dense and lexical retrieval. Modality-routed generation with page-level citations. Runs on a 4GB laptop GPU.
Multimodal RAG with per-query routing to text / visual / hybrid retrieval paths. Vision-LLM answers and regression-gated evals.
A high-performance RAG system for PDFs using multi-vector embeddings (ColPali / ColQwen / ColSmol) with vector search in Qdrant, prefetch optimization, and reranking for improved relevance. Designed for speed, accuracy, and scalability, this system is ideal for building intelligent search, document understanding, and QA applications.
Healthcare Multimodal RAG system for medical visual question answering and retrieval-augmented reasoning using LLaVA, QLoRA, OpenI chest X-rays, and scalable modular architecture with future ColQwen2, BM25, CLIP, RRF, and Qwen2-VL integration.
Visual RAG system for financial document analysis using ColQwen2.5, Qdrant, Claude Opus/Sonnet
VisRAG playground for finding your perfect embedding + VLM combo. Index PDFs with multimodal models, compare responses side-by-side.
Vision RAG over PDF pages: ColQwen2 + Qdrant retrieval, Gemini returns a bounding region that's cropped to show the exact chart slice an answer came from.
Sovereign multimodal RAG for German industrial documentation. EU AI Act-aware by design. Built with ColQwen2/ColPali, LangGraph, FastAPI, Next.js, pgvector.
To associate your repository with the colqwen2 topic, visit your repo's landing page and select "manage topics."