Added Recipe for Multimodal RAG System with Reranking and Quantized Vision Language Model on Consumer GPU #241
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…ent_retrieval_and_reranker_and_vlms
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View / edit / reply to this conversation on ReviewNB stevhliu commented on 2024-12-02T21:30:20Z I think this might be a little clearer.
"...by integrating ColQwen2 for document retrieval, MonoQwen2-VL-v0.1 for reranking, and Qwen2-VL as the vision language model (VLM)." |
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View / edit / reply to this conversation on ReviewNB stevhliu commented on 2024-12-02T21:30:20Z I think it would be nicer to link to https://huggingface.co/datasets/sergiopaniego/ourworldindata_example so users can preview some of the images they'll be using right from the browser |
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View / edit / reply to this conversation on ReviewNB stevhliu commented on 2024-12-02T21:30:21Z Would be helpful to add a sentence explaining what Byaldi is |
| @@ -27,6 +27,7 @@ Check out the recently added notebooks: | |||
| - [Multimodal Retrieval-Augmented Generation (RAG) with Document Retrieval (ColPali) and Vision Language Models (VLMs)](multimodal_rag_using_document_retrieval_and_vlms) | |||
| - [Fine-Tuning a Vision Language Model (Qwen2-VL-7B) with the Hugging Face Ecosystem (TRL)](fine_tuning_vlm_trl) | |||
| - [Multi-agent RAG System 🤖🤝🤖](multiagent_rag_system) | |||
| - [Multimodal RAG with ColQwen2, Reranker, and Quantized VLMs on Consumer GPUs](multimodal_rag_using_document_retrieval_and_reranker_and_vlms) | |||
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I've updated the recipe and |
What does this PR do?
Fixes #240
Who can review?
@merveenoyan and @stevhliu.