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https://github.com/IntelLabs/fastRAG
Efficient Retrieval Augmentation and Generation Framework
https://github.com/IntelLabs/fastRAG
benchmark colbert diffusion generative-ai information-retrieval knowledge-graph llm multi-modal nlp question-answering semantic-search sentence-transformers summarization transformers
Last synced: 2 months ago
JSON representation
Efficient Retrieval Augmentation and Generation Framework
- Host: GitHub
- URL: https://github.com/IntelLabs/fastRAG
- Owner: IntelLabs
- License: apache-2.0
- Created: 2023-01-23T16:25:35.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-05-22T15:13:25.000Z (8 months ago)
- Last Synced: 2024-05-22T16:29:22.077Z (8 months ago)
- Topics: benchmark, colbert, diffusion, generative-ai, information-retrieval, knowledge-graph, llm, multi-modal, nlp, question-answering, semantic-search, sentence-transformers, summarization, transformers
- Language: Python
- Homepage:
- Size: 20.3 MB
- Stars: 945
- Watchers: 10
- Forks: 75
- Open Issues: 3
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Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Citation: CITATION.cff
- Security: SECURITY.md
Awesome Lists containing this project
- awesome - IntelLabs/fastRAG - Efficient Retrieval Augmentation and Generation Framework (Python)
- awesome-oneapi - fastRAG - Build and explore efficient retrieval-augmented generative models and applications. It's main goal is to make retrieval augmented generation as efficient as possible through the use of state-of-the-art and efficient retrieval and generative models. (Table of Contents / AI - Natural Language Processing)
- ai-game-devtools - fastRAG
- awesome-production-machine-learning - fastRAG - fastRAG is a research framework for efficient and optimized retrieval augmented generative pipelines, incorporating state-of-the-art LLMs and Information Retrieval. (Neural Search and Retrieval)