Search Results for "rtx"
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Showing 20 open source projects for "rtx"
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NVIDIA Isaac Sim
NVIDIA Isaac Sim is an open-source application on NVIDIA Omniverse
NVIDIA Isaac Sim is a high-fidelity robotics simulation platform built on NVIDIA Omniverse to develop, test, and validate AI-driven robots in physically accurate virtual environments. It supports a wide array of robotics formats (URDF, MJCF, CAD), includes GPU-accelerated physics, and features immersive RTX rendering and multisensory simulation. Realistic physics via GPU-accelerated engines and RTX ray tracing. Multi-sensor simulation (RGB-D cameras, Lidar, Radar, IMU, contact sensors). Extensible via platform APIs and can integrate into custom USD-based simulators. -
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Wan2.2
Wan2.2: Open and Advanced Large-Scale Video Generative Model
...Wan2.2 also open-sources a 5-billion parameter high-compression VAE-based hybrid text-image-to-video (TI2V) model that supports 720P video generation at 24fps on consumer-grade GPUs like the RTX 4090. It supports multiple video generation tasks including text-to-video. -
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mise
Dev tools, env vars, task runner
Mise (formerly RTX) is a cross-language CLI tool and task runner that manages developer tools, environment variables, and project tasks in a unified configuration (mise.toml). It handles tool installation (e.g., Node, Python, Terraform), env var profiles, and repeatable command scripting. -
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Tiny CUDA Neural Networks
Lightning fast C++/CUDA neural network framework
...We provide a sample application where an image function (x,y) -> (R,G,B) is learned. The fully fused MLP component of this framework requires a very large amount of shared memory in its default configuration. It will likely only work on an RTX 3090, an RTX 2080 Ti, or high-end enterprise GPUs. Lower-end cards must reduce the n_neurons parameter or use the CutlassMLP (better compatibility but slower) instead. tiny-cuda-nn comes with a PyTorch extension that allows using the fast MLPs and input encodings from within a Python context. These bindings can be significantly faster than full Python implementations; in particular for the multiresolution hash encoding. -
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jamesob's guide to running SOTA LLMs
Everything I know about running LLMs locally
...It documents one developer’s local LLM setup, including hardware choices, GPU layout, storage, PCIe switches, kernel settings, and serving workflows. The repository compares budget levels ranging from dual RTX 3090 systems to high-end multi-GPU workstations with very large VRAM pools. It includes ready-to-run serving configurations for selected models and local speech-to-text workloads. The guide focuses on real deployment details such as Docker containers, model weight storage, GPU peer-to-peer behavior, and agentic workload performance. ... -
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TensorRT Node for ComfyUI
Enables the best performance on NVIDIA RTX Graphics Cards
ComfyUI_TensorRT is an extension that lets ComfyUI run AI inference through NVIDIA’s TensorRT, aiming to get faster, more efficient execution on supported GPUs. It bridges the gap between ComfyUI’s flexible, node-based workflows and TensorRT’s highly optimized engine format. The result is that complex diffusion or image-processing graphs can be accelerated without the user having to rewrite the pipeline. The repo typically includes instructions for converting models to TensorRT engines and... -
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WhisperSpeech
An Open Source text-to-speech system built by inverting Whisper
...The repository includes notebooks and scripts for inference, long-form synthesis, and finetuning, as well as pre-trained models and converted datasets hosted on Hugging Face. Performance optimizations like torch.compile, KV-caching, and architectural tweaks allow the main model to reach up to 12× real-time speed on a consumer RTX 4090. -
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L'editor di testo che evolve — Editor ricco per Windows con formattazione avanzata, tre formati di salvataggio, pubblicazione web e pastebin integrati. Gratuito e portabile.
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Biya Upscale
Free local 2x/4x AI image upscaling for Windows
Free portable Windows app for local 2x/4x image upscaling with Real-ESRGAN. Download the model once on first launch; inference runs on your PC with no cloud upload, account, or API key. Verified packaged setup: Windows 11 + NVIDIA RTX 2050 using DirectML only; other hardware is not independently verified. AI may invent or alter details, and small text may become less legible. The v1.0.0 ZIP is unsigned and may trigger a Windows security warning. Seeking independent testers: report Windows version/GPU, whether launch, model download and upscaling worked, processing time and errors at https://github.com/Biya-dev/Biya-Upscale/issues/1. ... -
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BackgroundMattingV2
Real-Time High-Resolution Background Matting
Official repository for the paper Real-Time High-Resolution Background Matting. Our model requires capturing an additional background image and produces state-of-the-art matting results at 4K 30fps and HD 60fps on an Nvidia RTX 2080 TI GPU. -
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GLM-130B
GLM-130B: An Open Bilingual Pre-Trained Model (ICLR 2023)
...Trained on over 400 billion tokens (200B English, 200B Chinese), it achieves performance surpassing GPT-3 175B, OPT-175B, and BLOOM-176B on multiple benchmarks, while also showing significant improvements on Chinese datasets compared to other large models. The model supports efficient inference via INT8 and INT4 quantization, reducing hardware requirements from 8× A100 GPUs to as little as a single server with 4× RTX 3090s. Built on the SwissArmyTransformer (SAT) framework and compatible with DeepSpeed and FasterTransformer, it supports high-speed inference (up to 2.5× faster) and reproducible evaluation across 30+ benchmark tasks. -
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LLaMA INT8
Quantized inference code for LLaMA models
...Parallelism constructs from the original code were removed to simplify single-machine execution. The author demonstrated LLaMA 13B running within roughly 24 GiB of GPU memory on an RTX 4090. Repetition-penalty controls and supporting utilities are included for text generation. The project is now mainly historical because its maintainer recommends Hugging Face Transformers for serious modern inference and training workloads. -
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DLSS2FSR
CyberFSR/PotatoFSR (FSR 2.1.2) for Games
Replacing DLSS 2.x with FSR 2.1.2 for various games such as Cyberpunk 2077, Red Dead Redemption 2, etc. It includes a DLL wrapper/injector (winmm.dll) to disable Nvidia GeForce RTX GPU checking, so AMD Radeon / Nvidia GTX users can enjoy the mod. Download the latest relase from Release Page. Extract the contents of the archive next to the game EXE file in your games folder. Make sure the game is running in DX12 mode. Download the latest relase from Release Page. Extract the contents of the archive next to the game EXE file in your games folder. -
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Inventory Hunter
Get notified as soon as your next CPU, GPU, or console is in stock
Inventory Hunter is a stock-monitoring bot for tracking hard-to-find products such as CPUs, GPUs, and game consoles. It was originally created to help the maintainer get notified when an RTX 3070 became available. The project is designed to run continuously on a Raspberry Pi, always-on PC, Mac, or Docker-capable environment. It uses configuration files for supported retailer and product checks, then sends alerts through services such as Discord, Slack, Telegram, or email. The tool is focused on notifications rather than being presented as an automated purchasing system. ... -
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SMJ remote controlled sockets
Use your arduino to control remote controlled sockets by SMJ.
...Step 1: Get a pack of "SMJ remote controlled sockets". Step 2: Allocate channels (A-D) and buttons (1-3) to lamps and gizmo's around your home. Step 3: Connect an Arduino to an Aurel Wireless RTX-MID-3V transceiver (see code for mapping). Step 4: Load sketch on your Arduino (v11 is latest). Step 5: Place batch file (Windows). Your com port might not be com3. Step 6: Set up windows task scheduler. Get fancy and use "Sunwait4Windows" for dusk/dawn scheduling. Button "D3" allows you to use the handset to turn a group of SMJ devices on or off. ... -
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EPANET-RTX
The EPANET Real Time Extension
** This project has moved to GitHub. ** ** https://github.com/OpenWaterAnalytics/epanet-rtx ** -
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Zen3D
Zen3D is a 3D engine and editor for creating games
Zen3D is a full 3D engine and editor to create games. It supports DX12/11/GL/Vulkan & Metal. It has a bespoke scripting language called ZenScript. It includes RTX support for Raytraced or Hybrid rendering. -
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Devstral Small 2
Lightweight 24B agentic coding model with vision and long context
Devstral Small 2 is a compact agentic language model designed for software engineering workflows, excelling at tool usage, codebase exploration, and multi-file editing. With 24B parameters and FP8 instruct tuning, it delivers strong instruction following while remaining lightweight enough for local and on-device deployment. The model achieves competitive performance on SWE-bench, validating its effectiveness for real-world coding and automation tasks. It introduces vision capabilities,... -
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Nemotron 3.5 Lightning
Efficient 30B MoE model for long-running agents and local inference
...The model supports context windows up to 1 million tokens, enabling long-running workflows and large-context reasoning. Its NVFP4 quantization reduces deployment requirements while targeting NVIDIA hardware ranging from DGX Spark and RTX 5090 systems to H100, H200, and GB200 accelerators. NVIDIA also provides DSpark, Multi-Token Prediction, and DFlash speculative decoding methods to accelerate text generation. It supports English, coding languages, Spanish, French, German, Italian, and Japanese, and is intended for commercially deployable AI applications. The model can run on a single DGX Spark or H100 and integrates with inference frameworks including vLLM.
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