Showing 7 open source projects for "gpu-z"

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  • 1
    NVIDIA AI Blueprint

    NVIDIA AI Blueprint

    Suite of reference architectures for building GPU-accelerated vision

    NVIDIA AI Blueprint is an AI blueprint for building GPU-accelerated video intelligence applications and vision agents. It combines accelerated vision microservices, vision language models, large language models, embeddings, and NVIDIA NIM microservices to process both stored and streaming video. The project is organized around real-time video intelligence, downstream analytics, and agentic offline processing.
    Downloads: 1 This Week
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  • 2
    autoresearch

    autoresearch

    AI agents autonomously run and improve ML experiments overnight

    ...The system centers on a simple workflow where the agent modifies a single training file while human researchers guide the process through a program.md instruction file. Designed to run on a single GPU, it keeps the research loop minimal and self-contained to make autonomous experimentation practical. Over time, the agent logs experiments, evaluates improvements, and gradually evolves the model through automated trial-and-error.
    Downloads: 0 This Week
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  • 3
    CogAgent

    CogAgent

    An open sourced end-to-end VLM-based GUI Agent

    CogAgent is a 9B-parameter bilingual vision-language GUI agent model based on GLM-4V-9B, trained with staged data curation, optimization, and strategy upgrades to improve perception, action prediction, and generalization across tasks. It focuses on operating real user interfaces from screenshots plus text, and follows a strict input–output format that returns structured actions, grounded operations, and optional sensitivity annotations. The model is designed for agent-style execution rather...
    Downloads: 15 This Week
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  • 4
    CUDA Agent

    CUDA Agent

    Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

    CUDA Agent is a research-driven agentic reinforcement learning system designed to automatically generate and optimize high-performance CUDA kernels for GPU workloads. The project addresses the long-standing challenge that efficient CUDA programming typically requires deep hardware expertise by training an autonomous coding agent capable of iterative improvement through execution feedback. Its architecture combines large-scale data synthesis, a skill-augmented CUDA development environment, and long-horizon reinforcement learning to build intrinsic optimization capability rather than relying on simple post-hoc tuning. ...
    Downloads: 0 This Week
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  • 5
    Diplomacy Cicero

    Diplomacy Cicero

    Code for Cicero, an AI agent that plays the game of Diplomacy

    ...It supports two variants: Cicero (which handles full “press” negotiation) and Diplodocus (a variant focused on no-press diplomacy) as described in the README. The codebase is implemented primarily in Python with performance-critical components in C++ (via pybind11 bindings) and is configured to run in a high‐GPU cluster environment. Configuration is managed via protobuf files to define tasks such as self-play, benchmark agent comparisons, and RL training. The project is now archived and read-only, reflecting that it is no longer actively developed but remains publicly available for research use.
    Downloads: 0 This Week
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  • 6
    StudioOllamaUI

    StudioOllamaUI

    StudioOllamaUI is a local, portable interface for Ollama

    ...No Python, no libraries, no drama. 100% Portable: Just like a portable browser. Unzip, run, and that's it. It doesn't clutter your registry or leave traces on your disk. AI for Everyone: No expensive GPU? No problem. Optimized to run smoothly on your CPU and RAM. Total Privacy: Everything stays on your machine. No data leaves for the cloud, and no hidden files are left on your system.
    Downloads: 12 This Week
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  • 7
    Email to Event - ETE

    Email to Event - ETE

    The python App/Skrypt automaticly add important events into calendar.

    ...*Email is using standart IMAP, Calendar use iCalendar API and authentification method. Fast setup: 1. Download and unpack 2. Install LM studio - recomended for GPU compute 3. Run run_setings.bat and set your authentificators for email***/calendar and etg. 4. Push button SAVE 5. Push button PLAN for add task to Time scheduler 6. Check by run run_ETE.bat **Model must understand your language, test before use! ***In emal seting(usualy on web) create a new folder and set auto COPY! More information and complete instalation guidein in READ ME file. ...
    Downloads: 0 This Week
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