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<img src="marqo.png" alt="Marqo Logo" /> |
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<h1 align="center"> |
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<b>Welcome to Marqo 🙌</b> |
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<b>Your Unified Platform for Embedding Generation and Search</b><br> |
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Marqo is an open-source platform designed to streamline embedding generation, search, and ranking, delivering state-of-the-art retrieval across multimodal data. Also available on <a href="https://www.marqo.ai/cloud">Marqo Cloud</a> for seamless integration and scalability into any application or service.<br> |
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<b>Explore Our Repositories</b><br> |
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<li><a href="https://github.com/marqo-ai/marqo">Marqo</a>: The core embedding generation and search engine.</li> |
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<li><a href="https://github.com/marqo-ai/GCL">GCL</a>: Generalized Contrastive Learning for multimodal retrieval.</li> |
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<li><a href="https://github.com/marqo-ai/marqo-FashionCLIP">FashionCLIP</a>: SOTA image and text embeddings for fashion search, recommendations and classification.</li> |
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<li><a href="https://github.com/marqo-ai/marqo-ecommerce-embeddings">Ecommerce embeddings</a>: SOTA image and text embeddings for ecommerce search, recommendations and classification.</li> |
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<li><a href="https://github.com/marqo-ai/ecommerce-search">Ecommerce search application</a>: SOTA multimodal search and recommendations application for ecommerce.</li> |
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<b>Our Latest Innovations</b><br> |
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<li><a href="https://www.marqo.ai/blog/introducing-marqos-ecommerce-embedding-models">Ecommerce product embeddings</a>: Our latest models for ecommerce retrieval.</li> |
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<li><a href="https://www.marqo.ai/blog/introducing-marqtune">Embedding Fine-Tuning with MarqTune</a>: Tailor embeddings to your domain for superior search results.</li> |
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<li><a href="https://www.marqo.ai/blog/search-model-for-fashion">FashionSigLIP</a>: Our latest model for fashion retrieval, combining cutting-edge techniques for enhanced search.</li> |
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<li><a href="https://www.marqo.ai/blog/generalized-contrastive-learning-for-multi-modal-retrieval-and-ranking?_gl=1*vkeuqm*_gcl_au*MTM0OTc4OTY4Ny4xNzIzNTQ0NTcy">Generalized Contrastive Learning (GCL)</a>: A framework for training robust embedding models for multimodal search. <a href="https://arxiv.org/abs/2404.08535">Read the GCL paper on arXiv.</a></li> |
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<li><a href="https://www.marqo.ai/blog/understanding-recall-in-hnsw-search">Understanding Recall in HNSW</a>: Insights into understanding and optimizing recall when using hierarchical navigable small worlds (HNSW) in vector search. <a href="https://arxiv.org/abs/2405.17813">Read the HNSW paper on arXiv.</a></li> |
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<li><a href="https://www.marqo.ai/blog/ui-concepts-for-vector-search">Designing Interfaces for Multimodal Vector Search Applications</a>:. Explore novel UI/UX concepts for implementing multi-modal vector search image search applications. <a href="https://arxiv.org/abs/2409.11629">Read the paper on arXiv.</a></li> |
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<li><a href="https://www.marqo.ai/blog/generalized-contrastive-learning-for-multi-modal-retrieval-and-ranking?_gl=1*vkeuqm*_gcl_au*MTM0OTc4OTY4Ny4xNzIzNTQ0NTcy">Marqo-GS-10M multimodal dataset</a>:. Open source multimodal product retrieval dataset of 10M query-product pairs with both text and images. <a href="https://huggingface.co/datasets/Marqo/marqo-GS-10M">Explore the dataset!</a></li> |
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