NovaSearch-Team/RAG-Retrieval
RAG-Retrieval
Unify Efficient Fine-tuning of RAG Retrieval, including Embedding, ColBERT, ReRanker.
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NovaSearch-Team
NovaSearch-Team • individual
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Created
Mar 16, 2024
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README Summary
<h1 align="center">RAG-Retrieval</h1> <p align="center"> <a href="https://pypi.org/project/rag-retrieval/#description"> <img alt="Build" src="https://img.shields.io/pypi/v/rag-retrieval?color=brightgreen"> </a> <!-- <a href="https://www.pepy.tech/projects/rag-retrieval"> <img alt="Build" src="https://static.pepy.tech/personalized-badge/rag-retrieval?period=total&units=international_system&left_color=grey&right_color=brightgreen&left_text=downloads"> </a> -
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ColBERT ArchitectureDense Passage RetrievalEmbedding Fine-tuningInformation RetrievalMulti-Vector RetrievalNeural RerankingRetrieval-Augmented GenerationTransfer Learning for IRVector Search Optimization
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ColBERT ArchitectureDense Passage RetrievalEmbedding Fine-tuningInformation RetrievalMulti-Vector RetrievalNeural RerankingRetrieval-Augmented GenerationTransfer Learning for IRVector Search OptimizationDeepSpeedDistillationEmbeddingsFSDPForkedGPU / CUDAHybrid SearchLarge Language ModelsOpen SourcePyTorchPythonRerankingResearch / PapersRoadmapTransformersTutorial
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Updated 11 months ago
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research- Quality
- medium
- Maturity
- research
Categories
Foundation ModelsPrimaryRAG & RetrievalModel TrainingInference & ServingSearch & KnowledgeLearning Resources
PM Skills
Product Discovery
Languages
Python100.0%
Timeline
- Project created
- Mar 16, 2024
- Forked
- Mar 29, 2026
- Your last push
- 11 months ago
- Upstream last push
- 23 days ago
- Tracked since
- Jul 5, 2025
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