Showing 2409 open source projects for "vnc windows to linux"

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  • 1
    CAG

    CAG

    Cache-Augmented Generation: A Simple, Efficient Alternative to RAG

    CAG, or Cache-Augmented Generation, is an experimental framework that explores an alternative architecture for integrating external knowledge into large language model responses. Traditional retrieval-augmented generation systems rely on real-time retrieval of documents from databases or vector stores during inference. CAG proposes a different approach by preloading relevant knowledge into the model’s context window and precomputing the model’s key-value cache before queries are processed....
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  • 2
    RLHF-Reward-Modeling

    RLHF-Reward-Modeling

    Recipes to train reward model for RLHF

    RLHF-Reward-Modeling is an open-source research framework focused on training reward models used in reinforcement learning from human feedback for large language models. In RLHF pipelines, reward models are responsible for evaluating generated responses and assigning scores that guide the model toward outputs that better match human preferences. The repository provides training recipes and implementations for building reward and preference models using modern machine learning frameworks. It...
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  • 3
    WFGY 3.0

    WFGY 3.0

    A tension reasoning engine over 131 S-class problems

    WFGY is an experimental open-source reasoning framework designed to improve the reliability and interpretability of large language model outputs through structured reasoning layers. The project introduces a conceptual reasoning engine that analyzes complex problems by identifying semantic compression errors and residual assumptions within a system’s reasoning process. Its architecture treats reasoning failures as measurable signals that can be detected and analyzed rather than simply...
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  • 4
    PKU Beaver

    PKU Beaver

    Constrained Value Alignment via Safe Reinforcement Learning

    PKU Beaver is an open-source research project focused on improving the safety alignment of large language models through reinforcement learning from human feedback under explicit safety constraints. The framework introduces techniques that separate helpfulness and harmlessness signals during training, allowing models to optimize for useful responses while minimizing harmful behavior. To support this process, the project provides datasets containing human-labeled examples that encode both...
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  • 5
    WebGLM

    WebGLM

    An Efficient Web-enhanced Question Answering System

    WebGLM is a web-enhanced question-answering system that combines a large language model with web search and retrieval capabilities to produce more accurate answers. The system is based on the General Language Model architecture and was designed to enable language models to interact directly with web information during the question-answering process. Instead of relying solely on knowledge stored in the model’s training data, the system retrieves relevant web content and integrates it into the...
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  • 6
    code-act

    code-act

    Official Repo for ICML 2024 paper

    code-act is a research framework for building intelligent language-model agents that interact with their environment through executable code actions. The system proposes a unified action representation where language models produce Python code that can be executed directly, allowing the model to interact with external tools and environments in a structured way. By integrating a Python interpreter with the agent architecture, the system enables the agent to execute code, observe the results,...
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  • 7
    ModernBERT

    ModernBERT

    Bringing BERT into modernity via both architecture changes and scaling

    ModernBERT is an open-source research project that modernizes the classic BERT encoder architecture by incorporating recent advances in transformer design, training techniques, and efficiency improvements. The goal of the project is to bring BERT-style models up to date with the capabilities of modern large language models while preserving the strengths of bidirectional encoder architectures used for tasks such as classification, retrieval, and semantic search. ModernBERT introduces...
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  • 8
    LLMCompiler

    LLMCompiler

    An LLM Compiler for Parallel Function Calling

    LLMCompiler is an open-source framework designed to optimize how large language models orchestrate multiple external tool or function calls during complex reasoning tasks. Traditional LLM agent systems typically execute tool calls sequentially, which can create latency, higher costs, and reduced reliability when solving multi-step problems. LLMCompiler addresses this limitation by applying principles from classical compilers to analyze a task and construct an execution plan that allows...
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  • 9
    PRIME

    PRIME

    Scalable RL solution for advanced reasoning of language models

    PRIME is an open-source reinforcement learning framework designed to improve the reasoning capabilities of large language models through process-level rewards rather than relying only on final outputs. The system introduces the concept of process reinforcement through implicit rewards, allowing models to receive feedback on intermediate reasoning steps instead of evaluating only the final answer. This approach helps models learn better reasoning strategies and encourages them to generate...
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  • 10
    AI Powered Knowledge Graph Generator

    AI Powered Knowledge Graph Generator

    AI Powered Knowledge Graph Generator

    AI-Powered Knowledge Graph is an open-source project focused on building knowledge graph systems that integrate artificial intelligence and machine learning to represent complex relationships between data entities. Knowledge graphs organize information as networks of nodes and relationships, allowing applications to analyze connections between concepts, datasets, or real-world entities. By incorporating AI techniques such as natural language processing and semantic reasoning, the project...
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  • 11
    Agentless

    Agentless

    An agentless approach to automatically solve software development

    Agentless is an open-source framework that applies large language models to automatically resolve software development issues without relying on complex autonomous agent systems. The project proposes an alternative approach to AI-driven code repair that avoids the overhead of multi-agent orchestration by using a structured pipeline for identifying and fixing bugs. When solving a problem, the system first performs localization to determine which files, functions, or code segments are most...
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  • 12
    Magicoder

    Magicoder

    Empowering Code Generation with OSS-Instruct

    Magicoder is an open-source family of large language models designed specifically for code generation and software development tasks. The project focuses on improving the quality and diversity of code generation by training models with a novel dataset construction approach known as OSS-Instruct. This technique uses open-source code repositories as a foundation for generating more realistic and diverse instruction datasets for training language models. By grounding training data in real...
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  • 13
    MaxText

    MaxText

    A simple, performant and scalable Jax LLM

    MaxText is a high-performance, highly scalable open-source framework designed to train and fine-tune large language models using the JAX ecosystem. The project acts as both a reference implementation and a practical training library that demonstrates best practices for building and scaling transformer-based language models on modern accelerator hardware. It is optimized to run efficiently on Google Cloud TPUs and GPUs, enabling researchers and engineers to train models ranging from small...
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  • 14
    LISA

    LISA

    LISA: Reasoning Segmentation via Large Language Model

    LISA is an open-source multimodal AI system designed to enable language models to perform pixel-level reasoning and segmentation tasks on images. The project introduces a framework where a large language model can interpret natural language instructions and produce segmentation masks that highlight relevant regions in an image. Instead of relying solely on predefined object categories, the model is capable of reasoning about complex textual queries and translating them into visual...
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  • 15
    LLM Guard

    LLM Guard

    The Security Toolkit for LLM Interactions

    LLM Guard is an open-source security toolkit designed to protect large language model applications from various security risks and adversarial attacks. The library acts as a protective layer between users and language models by analyzing inputs and outputs before they reach or leave the model. It includes scanning mechanisms that detect malicious prompts, prompt injection attempts, toxic content, and other harmful inputs that could compromise AI systems. The toolkit also helps prevent...
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  • 16
    InternLM-XComposer-2.5

    InternLM-XComposer-2.5

    InternLM-XComposer2.5-OmniLive: A Comprehensive Multimodal System

    InternLM-XComposer is an open-source multimodal AI system designed to generate long-form content that combines text with visual elements such as images and diagrams. The model is built on top of the InternLM language model architecture and extends its capabilities to handle multimodal inputs and outputs. Instead of producing only textual responses, the system can generate visually enriched documents such as illustrated articles, presentations, and educational materials. It incorporates...
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  • 17
    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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  • 18
    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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  • 19
    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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  • 20
    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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  • 21
    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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  • 22
    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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  • 23
    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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  • 24
    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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  • 25
    llms-from-scratch-cn

    llms-from-scratch-cn

    Build a large language model from 0 only with Python foundation

    llms-from-scratch-cn is an educational open-source project designed to teach developers how to build large language models step by step using practical code and conceptual explanations. The repository provides a hands-on learning path that begins with the fundamentals of natural language processing and gradually progresses toward implementing full GPT-style architectures from the ground up. Rather than focusing on using pre-trained models through APIs, the project emphasizes understanding...
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