Showing 7405 open source projects for "linux-debian"

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  • 1
    text-extract-api

    text-extract-api

    Document (PDF, Word, PPTX ...) extraction and parse API

    text-extract-api is an open-source service designed to extract readable text from a wide variety of document formats through a simple API interface. The project focuses on converting complex files such as PDFs, images, scanned documents, and office files into structured plain text that can be processed by downstream applications or language models. Instead of requiring developers to integrate multiple document parsing libraries individually, the system centralizes text extraction...
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  • 2
    MatMul-Free LM

    MatMul-Free LM

    Implementation for MatMul-free LM

    MatMul-Free LM is an experimental implementation of a large language model architecture designed to eliminate traditional matrix multiplication operations used in transformer networks. Since matrix multiplication is one of the most computationally expensive components of modern language models, the project explores alternative computational strategies that reduce hardware requirements while maintaining comparable performance. The architecture relies on quantization-aware training and...
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  • 3
    Hallucination Leaderboard

    Hallucination Leaderboard

    Leaderboard Comparing LLM Performance at Producing Hallucinations

    Hallucination Leaderboard is an open research project that tracks and compares the tendency of large language models to produce hallucinated or inaccurate information when generating summaries. The project provides a standardized benchmark that evaluates different models using a dedicated hallucination detection system known as the Hallucination Evaluation Model. Each model is tested on document summarization tasks to measure how often generated responses introduce information that is not...
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  • 4
    Skywork-R1V4

    Skywork-R1V4

    Skywork-R1V is an advanced multimodal AI model series

    Skywork-R1V is an open-source multimodal reasoning model designed to extend the capabilities of large language models into vision-language tasks that require complex logical reasoning. The project introduces a model architecture that transfers the reasoning abilities of advanced text-based models into visual domains so the system can interpret images and perform multi-step reasoning about them. Instead of retraining both language and vision models from scratch, the framework uses a...
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  • 5
    AgentBench

    AgentBench

    A Comprehensive Benchmark to Evaluate LLMs as Agents (ICLR'24)

    AgentBench is an open-source benchmark designed to evaluate the capabilities of large language models when used as autonomous agents. Unlike traditional language model benchmarks that focus on static text tasks, AgentBench measures how models perform in interactive environments that require planning, reasoning, and decision-making. The benchmark includes multiple environments that simulate realistic scenarios such as web interaction, database querying, and problem solving tasks. These...
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  • 6
    AI Agents From Scratch

    AI Agents From Scratch

    Demystify AI agents by building them yourself. Local LLMs

    AI Agents from Scratch is an educational repository designed to teach developers how to build autonomous AI agents using large language models and modern AI frameworks. The project walks through the process of constructing agents step by step, beginning with simple prompt-based interactions and gradually introducing more advanced capabilities such as planning, tool use, and memory. The repository provides example implementations that demonstrate how language models can interact with external...
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  • 7
    Torch Pruning

    Torch Pruning

    DepGraph: Towards Any Structural Pruning

    Torch-Pruning is an open-source toolkit designed to optimize deep neural networks by performing structural pruning directly within PyTorch models. The library focuses on reducing the size and computational cost of neural networks by removing redundant parameters and channels while maintaining model performance. It introduces a graph-based algorithm called DepGraph that automatically identifies dependencies between layers, allowing parameters to be pruned safely across complex architectures....
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  • 8
    vLLM Semantic Router

    vLLM Semantic Router

    System Level Intelligent Router for Mixture-of-Models at Cloud

    Semantic Router is an open-source system designed to intelligently route requests across multiple large language models based on the semantic meaning and complexity of user queries. Instead of sending every prompt to the same model, the system analyzes the intent and reasoning requirements of the request and dynamically selects the most appropriate model to process it. This approach allows developers to combine multiple models with different strengths, such as lightweight models for simple...
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  • 9
    Chitu

    Chitu

    High-performance inference framework for large language models

    Chitu is a high-performance inference engine designed to deploy and run large language models efficiently in production environments. The framework focuses on improving efficiency, flexibility, and scalability for organizations that need to run LLM inference workloads across different hardware platforms. It supports heterogeneous computing environments, including CPUs, GPUs, and various specialized AI accelerators, allowing models to run across a wide range of infrastructure configurations....
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  • 10
    Daily Interview

    Daily Interview

    Datawhale members have compiled a book covering machine learning

    daily-interview is an open-source educational repository designed to help software engineers prepare for technical interviews through daily practice questions and curated learning materials. The project collects a wide range of interview questions related to algorithms, data structures, system design, and core computer science topics commonly tested by technology companies. The repository is organized in a structured format that encourages developers to practice solving problems regularly...
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  • 11
    In-The-Wild Jailbreak Prompts on LLMs

    In-The-Wild Jailbreak Prompts on LLMs

    A dataset consists of 15,140 ChatGPT prompts from Reddit

    In-The-Wild Jailbreak Prompts on LLMs is an open-source research repository that provides datasets and analytical tools for studying jailbreak prompts used to bypass safety restrictions in large language models. The project is part of a research effort to understand how users attempt to circumvent alignment and safety mechanisms built into modern AI systems. The repository includes a large collection of prompts gathered from real-world platforms such as Reddit, Discord, prompt-sharing...
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  • 12
    NExT-GPT

    NExT-GPT

    Code and models for ICML 2024 paper, NExT-GPT

    NExT-GPT is an open-source research framework that implements an advanced multimodal large language model capable of understanding and generating content across multiple modalities. Unlike traditional models that primarily handle text, NExT-GPT supports input and output combinations involving text, images, video, and audio in a unified architecture. The system connects a large language model with multimodal encoders and diffusion-based decoders so it can interpret information from different...
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  • 13
    Chat with LLMs Everywhere

    Chat with LLMs Everywhere

    Run PyTorch LLMs locally on servers, desktop and mobile

    TorchChat is an open-source project from the PyTorch ecosystem designed to demonstrate how large language models can be executed efficiently across different computing environments. The project provides a compact codebase that illustrates how to run conversational AI systems using PyTorch models on laptops, servers, and mobile devices. It is intended primarily as a reference implementation that shows developers how to integrate large language models into applications without requiring a...
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  • 14
    FastDeploy

    FastDeploy

    High-performance Inference and Deployment Toolkit for LLMs and VLMs

    FastDeploy is an open-source inference and deployment toolkit designed to simplify the process of running and serving deep learning models across a wide range of hardware platforms. Developed within the PaddlePaddle ecosystem, the toolkit focuses on providing high-performance deployment capabilities for modern AI models including large language models and vision-language systems. The platform enables developers to deploy trained models quickly using optimized inference pipelines that support...
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  • 15
    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...
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  • 16
    RubyLLM

    RubyLLM

    One beautiful Ruby API for OpenAI, Anthropic, Gemini, Bedrock

    RubyLLM is an open-source Ruby library that provides a unified API for interacting with multiple large language model providers through a single, consistent interface. The library is designed to simplify the process of integrating AI capabilities into Ruby applications by abstracting away differences between model providers and API formats. Developers can use RubyLLM to communicate with a wide range of AI services including OpenAI, Anthropic, Google Gemini, Mistral, Ollama, and other...
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  • 17
    Osaurus

    Osaurus

    AI edge infrastructure for macOS. Run local or cloud models

    Osaurus is an open-source AI edge infrastructure platform designed specifically for macOS environments to run and manage AI models locally. The project provides a native runtime that allows applications to access large language models and AI tools directly on the user’s machine without relying entirely on cloud services. Osaurus supports running both local and remote models, enabling developers to build AI-powered applications that can operate offline or leverage external APIs when needed....
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  • 18
    LLM Workflow Engine

    LLM Workflow Engine

    Power CLI and Workflow manager for LLMs (core package)

    LLM Workflow Engine is an open-source command-line framework designed to integrate large language models into automated workflows and developer environments. The platform allows users to interact with AI models directly from the terminal, enabling conversational AI access through shell commands and scripts. Instead of focusing solely on chat interactions, the system is built to embed LLM calls into larger automation pipelines where model outputs can drive decision making or trigger...
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  • 19
    ClaraVerse

    ClaraVerse

    Claraverse is a opesource privacy focused ecosystem to replace ChatGPT

    ClaraVerse is an open-source private AI workspace designed to give users a unified environment for interacting with large language models, building automations, and managing AI-driven tasks in a self-hosted environment. The platform combines chat interfaces, workflow automation, and long-running task management into a single application that can connect to both local and cloud-based AI models. Users can integrate models from multiple providers such as OpenAI, Anthropic, Google, or locally...
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  • 20
    ai-cookbook

    ai-cookbook

    Examples and tutorials to help developers build AI systems

    ai-cookbook is an open-source repository that provides practical tutorials, code examples, and reusable snippets designed to help developers build real-world artificial intelligence applications quickly. The project focuses on delivering hands-on engineering guidance rather than theoretical explanations, allowing developers to copy, adapt, and integrate working code directly into their own systems. The repository contains examples that demonstrate how to build AI workflows using modern tools...
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  • 21
    LightLLM

    LightLLM

    LightLLM is a Python-based LLM (Large Language Model) inference

    LightLLM is a high-performance inference and serving framework designed specifically for large language models, focusing on lightweight architecture, scalability, and efficient deployment. The framework enables developers to run and serve modern language models with significantly improved speed and resource efficiency compared to many traditional inference systems. Built primarily in Python, the project integrates optimization techniques and ideas from several leading open-source...
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  • 22
    PyTorch-Tutorial-2nd

    PyTorch-Tutorial-2nd

    CV, NLP, LLM project applications, and advanced engineering deployment

    PyTorch-Tutorial-2nd is an open-source educational repository that provides structured tutorials for learning deep learning with the PyTorch framework. The project serves as a practical companion to a second edition of a PyTorch learning guide and is designed to help learners understand neural network concepts through hands-on coding examples. The repository covers a wide range of topics including tensor operations, neural network construction, model training workflows, and optimization...
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  • 23
    Huatuo-Llama-Med-Chinese

    Huatuo-Llama-Med-Chinese

    Instruction-tuning LLM with Chinese Medical Knowledge

    Huatuo-Llama-Med-Chinese is an open-source project that develops medical-domain large language models by instruction-tuning existing models using Chinese medical knowledge. The project builds specialized models by fine-tuning architectures such as LLaMA, Alpaca-Chinese, and Bloom with curated medical datasets. These datasets are constructed from medical knowledge graphs, academic literature, and question-answer pairs designed to teach models how to respond accurately to healthcare-related...
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  • 24
    Xtuner

    Xtuner

    A Next-Generation Training Engine Built for Ultra-Large MoE Models

    Xtuner is a large-scale training engine designed for efficient training and fine-tuning of modern large language models, particularly mixture-of-experts architectures. The framework focuses on enabling scalable training for extremely large models while maintaining efficiency across distributed computing environments. Unlike traditional 3D parallel training strategies, XTuner introduces optimized parallelism techniques that simplify scaling and reduce system complexity when training massive...
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  • 25
    Sparrow

    Sparrow

    Structured data extraction and instruction calling with ML, LLM

    Sparrow is an open-source platform designed to extract structured information from documents, images, and other unstructured data sources using machine learning and large language models. The system focuses on transforming complex documents such as invoices, receipts, forms, and scanned pages into structured formats like JSON that can be processed by downstream applications. It combines several components, including OCR pipelines, vision-language models, and LLM-based reasoning modules to...
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