Add vectors to Hub datasets and do in memory vector search.
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Create visual diagrams and flowcharts easily
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Ask questions about images
Demo for MiniCPM-o 2.6 to answer questions about images
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Answer questions about documents or images
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Ask questions about images and get detailed answers
A private and powerful multimodal AI chatbot that runs local
Generate answers using images or videos
Ivy-VL is a lightweight multimodal model with only 3B.
Vectorsearch Hub Datasets is a tool designed to enhance your dataset management and analysis capabilities by enabling vector-based searches. It allows you to add vector representations to your datasets stored on Hugging Face Hub and perform in-memory vector searches for efficient and accurate results. This tool is particularly useful for tasks like visual question answering (VQA), where vector similarity plays a crucial role in matching images or embeddings.
1. What are the benefits of using Vectorsearch Hub Datasets?
Vectorsearch Hub Datasets allows for efficient and accurate vector-based searches, enabling you to uncover patterns and relationships within your datasets quickly. It’s ideal for tasks like VQA and similarity-based analysis.
2. Can I use custom vectorization methods?
Yes, Vectorsearch Hub Datasets supports custom vectorization pipelines, giving you flexibility in how you process and represent your data.
3. Is Vectorsearch Hub Datasets suitable for large-scale datasets?
Yes, the tool is optimized for performance and can handle large-scale datasets with ease, making it a robust choice for big data applications.