Showing 15 open source projects for "virtual-machine"

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  • 1
    Weaviate

    Weaviate

    Weaviate is a cloud-native, modular, real-time vector search engine

    Weaviate in a nutshell: Weaviate is a vector search engine and vector database. Weaviate uses machine learning to vectorize and store data, and to find answers to natural language queries. With Weaviate you can also bring your custom ML models to production scale. Weaviate in detail: Weaviate is a low-latency vector search engine with out-of-the-box support for different media types (text, images, etc.). It offers Semantic Search, Question-Answer-Extraction, Classification, Customizable Models (PyTorch/TensorFlow/Keras), and more. ...
    Downloads: 1 This Week
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  • 2
    txtai

    txtai

    Build AI-powered semantic search applications

    txtai executes machine-learning workflows to transform data and build AI-powered semantic search applications. Traditional search systems use keywords to find data. Semantic search applications have an understanding of natural language and identify results that have the same meaning, not necessarily the same keywords. Backed by state-of-the-art machine learning models, data is transformed into vector representations for search (also known as embeddings).
    Downloads: 0 This Week
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  • 3
    Semantra

    Semantra

    Multi-tool for semantic search

    Semantra is an open-source semantic search tool designed to help users explore large collections of documents by meaning rather than simple keyword matching. The software analyzes text and PDF documents stored locally and creates embeddings that allow queries to retrieve results based on conceptual similarity. It is primarily intended for individuals who need to extract insights from large document collections, including researchers, journalists, students, and historians. The system runs...
    Downloads: 0 This Week
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  • 4
    QMD

    QMD

    mini cli search engine for your docs, knowledge bases, etc.

    ...Users can organize content into named collections, embed documents for semantic retrieval, and then perform keyword searches, semantic searches, or hybrid natural-language queries to quickly surface the most useful information across all indexed sources. Because the entire system runs on the user’s machine, privacy is preserved and there’s no risk of exposing sensitive content to outside providers.
    Downloads: 4 This Week
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  • 5
    ModernBERT

    ModernBERT

    Bringing BERT into modernity via both architecture changes and scaling

    ...ModernBERT introduces architectural improvements that enhance both training efficiency and inference performance, making the model more suitable for modern large-scale machine learning pipelines. The repository also includes FlexBERT, a modular framework that allows developers to experiment with different encoder building blocks and configurations when constructing new models.
    Downloads: 2 This Week
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  • 6
    Python Client For NLP Cloud

    Python Client For NLP Cloud

    NLP Cloud serves high performance pre-trained or custom models for NER

    NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, dialogue summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, blog post generation, source code generation, question answering, automatic speech recognition, machine translation, language detection, semantic search, semantic similarity, tokenization, POS tagging, embeddings, and dependency parsing. It is ready for production, served through a REST API. You can either use the NLP Cloud pre-trained models, fine-tune your own models, or deploy your own models.
    Downloads: 0 This Week
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  • 7
    MyScaleDB

    MyScaleDB

    A @ClickHouse fork that supports high-performance vector search

    MyScaleDB is an open-source SQL vector database designed for building large-scale AI and machine learning applications that require both analytical queries and semantic vector search. The system is built on top of the ClickHouse database engine and extends it with specialized indexing and search capabilities optimized for vector embeddings. This design allows developers to store structured data, unstructured text, and high-dimensional vector embeddings within a single database platform. ...
    Downloads: 0 This Week
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  • 8
    Pixeltable

    Pixeltable

    Data Infrastructure providing an approach to multimodal AI workloads

    Pixeltable is an open-source Python data infrastructure framework designed to support the development of multimodal AI applications. The system provides a declarative interface for managing the entire lifecycle of AI data pipelines, including storage, transformation, indexing, retrieval, and orchestration of datasets. Unlike traditional architectures that require multiple tools such as databases, vector stores, and workflow orchestrators, Pixeltable unifies these functions within a...
    Downloads: 0 This Week
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  • 9
    grepai

    grepai

    Semantic Search & Call Graphs for AI Agents

    ...In addition to semantic search, grepai offers call graph tracing so developers can understand which functions call or are called by others, aiding impact analysis and confident refactoring. Because it runs 100 % locally, your codebase never leaves your machine, preserving privacy and security while supporting AI agents and custom integrations.
    Downloads: 0 This Week
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  • 10
    Node.js Client For NLP Cloud

    Node.js Client For NLP Cloud

    NLP Cloud serves high performance pre-trained or custom models

    ...NLP Cloud serves high-performance pre-trained or custom models for NER, sentiment analysis, classification, summarization, dialogue summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, blog post generation, text generation, question answering, automatic speech recognition, machine translation, language detection, semantic search, semantic similarity, tokenization, POS tagging, embeddings, and dependency parsing. It is ready for production, and served through a REST API. You can either use the NLP Cloud pre-trained models, fine-tune your own models, or deploy your own models.
    Downloads: 0 This Week
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  • 11
    PHP Client For NLP Cloud

    PHP Client For NLP Cloud

    NLP Cloud serves high performance pre-trained or custom models for NER

    NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, dialogue summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, blog post generation, code generation, question answering, automatic speech recognition, machine translation, language detection, semantic search, semantic similarity, tokenization, POS tagging, embeddings, and dependency parsing. It is ready for production, served through a REST API. You can either use the NLP Cloud pre-trained models, fine-tune your own models, or deploy your own models. Pass the model you want to use and the NLP Cloud token to the client during initialization. ...
    Downloads: 0 This Week
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  • 12
    Hugging Face Transformer

    Hugging Face Transformer

    CPU/GPU inference server for Hugging Face transformer models

    Optimize and deploy in production Hugging Face Transformer models in a single command line. At Lefebvre Dalloz we run in-production semantic search engines in the legal domain, in the non-marketing language it's a re-ranker, and we based ours on Transformer. In that setup, latency is key to providing a good user experience, and relevancy inference is done online for hundreds of snippets per user query. Most tutorials on Transformer deployment in production are built over Pytorch and FastAPI....
    Downloads: 1 This Week
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  • 13
    hora

    hora

    Efficient approximate nearest neighbor search algorithm collections

    hora is an open-source high-performance vector similarity search library designed for large-scale machine learning and information retrieval systems. The project focuses on approximate nearest neighbor search, a fundamental technique used in modern AI applications such as recommendation systems, image search, and semantic search engines. Hora implements multiple efficient indexing algorithms that allow systems to rapidly search through high-dimensional vectors produced by machine learning models. ...
    Downloads: 0 This Week
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  • 14
    Vector AI

    Vector AI

    A platform for building vector based applications

    ...Create, store, manipulate, search and analyze vectors alongside json documents to power applications such as neural search, semantic search, personalized recommendations etc. Image2Vec, Audio2Vec, etc (Any data can be turned into vectors through machine learning). Store your vectors alongside documents without having to do a db lookup for metadata about the vectors. Enable searching of vectors and rich multimedia with vector similarity search. The backbone of many popular A.I use cases like reverse image search, recommendations, personalization, etc. There are scenarios where vector search is not as effective as traditional search, e.g. searching for skus. ...
    Downloads: 1 This Week
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  • 15
    LibrePhotos

    LibrePhotos

    A self-hosted open source photo management service

    LibrePhotos is an open-source self-hosted photo management platform designed to organize, browse, and analyze personal media libraries while preserving user privacy. The system allows individuals to store and manage their photos and videos locally rather than relying on commercial cloud services. It provides features similar to services like Google Photos but runs on a private server controlled by the user. The application includes AI-powered tools that automatically analyze images to detect...
    Downloads: 2 This Week
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