Showing 9 open source projects for "collections"

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  • 1
    MetaScreener

    MetaScreener

    AI-powered tool for efficient abstract and PDF screening

    MetaScreener is an open-source AI-assisted tool designed to streamline the screening process in systematic literature reviews and academic research workflows. The system helps researchers analyze large collections of academic abstracts and research papers to determine which studies are relevant for inclusion in evidence synthesis projects. Instead of manually reviewing hundreds or thousands of documents, researchers can use MetaScreener to apply machine learning techniques that assist with classification and prioritization of candidate papers. ...
    Downloads: 0 This Week
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  • 2
    DocETL

    DocETL

    A system for agentic LLM-powered data processing and ETL

    DocETL is an open-source system designed to build and execute data processing pipelines powered by large language models, particularly for analyzing complex collections of documents and unstructured datasets. The platform allows developers and researchers to construct structured workflows that extract, transform, and organize information from sources such as reports, transcripts, legal documents, and other text-heavy data. Instead of relying on single prompts or ad-hoc scripts, DocETL provides a declarative pipeline framework that breaks complex document analysis tasks into manageable operations that can be optimized and orchestrated automatically. ...
    Downloads: 0 This Week
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  • 3
    NVIDIA NeMo

    NVIDIA NeMo

    Toolkit for conversational AI

    NVIDIA NeMo, part of the NVIDIA AI platform, is a toolkit for building new state-of-the-art conversational AI models. NeMo has separate collections for Automatic Speech Recognition (ASR), Natural Language Processing (NLP), and Text-to-Speech (TTS) models. Each collection consists of prebuilt modules that include everything needed to train on your data. Every module can easily be customized, extended, and composed to create new conversational AI model architectures. Conversational AI architectures are typically large and require a lot of data and compute for training. ...
    Downloads: 4 This Week
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  • 4
    LLM-Aided OCR Project

    LLM-Aided OCR Project

    Enhances Tesseract OCR output using LLMs (local or API)

    LLM Aided OCR is an open-source system designed to improve optical character recognition accuracy by combining traditional OCR tools with large language models. The project addresses common OCR challenges such as distorted text, unusual fonts, historical documents, and complex layouts that often produce inaccurate results with standard OCR pipelines. The system first extracts raw text using OCR engines and then applies language models to analyze and correct recognition errors based on...
    Downloads: 1 This Week
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  • MongoDB Atlas runs apps anywhere Icon
    MongoDB Atlas runs apps anywhere

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  • 5
    In-The-Wild Jailbreak Prompts on LLMs

    In-The-Wild Jailbreak Prompts on LLMs

    A dataset consists of 15,140 ChatGPT prompts from Reddit

    ...Researchers analyze these prompts to identify patterns, attack strategies, and techniques commonly used to trick language models into producing restricted or harmful outputs. The dataset includes thousands of prompts collected across multiple platforms and represents one of the largest collections of jailbreak attempts available for research.
    Downloads: 1 This Week
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  • 6
    SimpleMem

    SimpleMem

    SimpleMem: Efficient Lifelong Memory for LLM Agents

    ...Unlike monolithic systems where memory management is ad-hoc, SimpleMem formalizes a memory lifecycle—write, index, retrieve, refine—so applications can handle user history, document collections, or dynamic contextual state systematically. It supports customizable embedding models, efficient vector indexes, and relevance weighting, making it practical for building assistants, personal agents, or domain-specific retrieval systems that need persistent knowledge.
    Downloads: 0 This Week
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  • 7
    Anomaly Detection Learning Resources

    Anomaly Detection Learning Resources

    Anomaly detection related books, papers, videos, and toolboxes

    Anomaly Detection Learning Resources is a curated open-source repository that collects educational materials, tools, and academic references related to anomaly detection and outlier analysis in data science. The project serves as a centralized index for researchers and practitioners who want to explore algorithms, datasets, and publications associated with detecting unusual patterns in data. The repository organizes resources into structured categories such as books, tutorials, academic...
    Downloads: 0 This Week
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  • 8
    InternVL

    InternVL

    A Pioneering Open-Source Alternative to GPT-4o

    ...The project focuses on scaling vision models and aligning them with large language models so that they can perform tasks involving both visual and textual information. InternVL is trained on massive collections of image-text data, enabling it to learn representations that capture both visual patterns and semantic meaning. The model supports a wide variety of tasks, including visual perception, image classification, and cross-modal retrieval between images and text. It can also be connected to language models to enable conversational interfaces that understand images, videos, and other visual content. ...
    Downloads: 0 This Week
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  • 9
    RAGxplorer

    RAGxplorer

    Open-source tool to visualise your RAG

    RAGxplorer is an open-source visualization tool designed to help developers analyze and understand Retrieval-Augmented Generation (RAG) pipelines. Retrieval-augmented generation combines language models with external document retrieval systems in order to produce more accurate and grounded responses. However, RAG systems can be complex because they involve multiple components such as embedding models, vector databases, and retrieval algorithms. RAGxplorer provides visual tools that allow...
    Downloads: 0 This Week
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    Train ML Models With SQL You Already Know

    BigQuery automates data prep, analysis, and predictions with built-in AI assistance.

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