Popular GitHub Repositories for Rtx 5090

Video, Image and GIF upscale/enlarge(Super-Resolution) and Video frame interpolation. Achieved with Waifu2x, Real-ESRGAN, Real-CUGAN, RTX Video Super Resolution VSR, SRMD, RealSR, Anime4K, RIFE, IFRNet, CAIN, DAIN, and ACNet.

High-performance Text-to-Speech server with OpenAI-compatible API, 8 voices, emotion tags, and modern web UI. Optimized for RTX GPUs.

ECN 5090- Machine Learning in Economics and Finance (Python)

vLLM-5090: Docker Container for RTX 5090 on WSL2/Windows

Chat With RTX Python API

A Gradio-based GUI for enhancing old/low-quality videos with NVIDIA RTX technology. Using Maxine Video Effects SDK, this tool applies AI-powered Super Resolution and Artifact Reduction. Perfect for restoring vintage videos and enhancing low-resolution footage with real-time GPU acceleration.

Cross-platform installer for Triton and SageAttention on ComfyUI. Simplifies GPU-accelerated inference setup for Windows users with automated dependency management and RTX 5090 support.

Multi-Modal Multi-Embodied Hivemind-like Iteration of RTX-2

The intelligent OptiScaler installer Linux gamers needed. Automates FSR4, XeSS & DLSS configuration with GPU-optimized profiles for RDNA3/4, Arc & RTX cards.

SaleFore AI: Ultra-accurate sales forecasting using ensemble ML (XGBoost, LightGBM, CatBoost) with RTX 4060 GPU optimization. Achieves 88-95% accuracy with advanced hyperparameter tuning.

Open source DIY AI computing platform: Build a powerful RTX 3090 GPU rig under €1,300 for local LLM inference, training, and AI development. Complete with parts list, assembly guide, Ubuntu setup, and remote access configuration. Ideal for students, researchers, and hobbyists wanting affordable AI hardware without cloud dependencies.

An Agentic AI Research Playground for building AI Agents and Mult-Agent systems leveraging open-source models, libraries, and frameworks. Models used to run agents locally on Nvidia RTX A2000 GPU - 8GB VRAM include the quantized Ollama models: llama3.1:8b-instruct-q8_0, llama3.1:8b_q8_0, qwen2.5:7b-instruct-q8_0, and qwen2.5-coder:7b-instruct-q8_0.

Prebuilt PyTorch 2.9.0 for CUDA 12.8 + sm_120 (RTX 5080)

CLI tool to apply NVIDIA RTX VSR upscale and TrueHDR tone-mapping to any video files

A cleaner, modernized reboot of Real-ESRGAN focused on best practices, up-to-date hardware support, and pragmatic developer ergonomics. Supports RTX 50-series (Blackwell) GPUs with automatic device selection, CPU fallback, and improved inference pipelines for both images and videos.

Bidirectional fine-tuning of Microsoft's Phi-3-Mini model for payment transaction processing using LoRA. Includes forward (structured→NL) and reverse (NL→structured) models. Optimized for NVIDIA RTX 3060 (12GB VRAM). 500 synthetic examples, ~95% accuracy, 30-60min training time.

LLM pipeline: data→tokenizer→attention→GPT train/eval→instruction FT→sampling. Reproducible, clean configs, RTX-4060 defaults, ready for AMP/LoRA/DDP.

A lightweight local AI assistant that lets you chat with your files — PDFs, documents, images, videos, and code — using semantic search, embeddings, OCR, and multimodal LLMs. Optimized to run on modest GPUs (e.g., RTX 3050 4GB) without requiring heavy VRAM like ChatRTX.

Docker Desktop for Windows + NVIDIA GeForce RTX シリーズの GPU 搭載 PC 向け dlshogi/ふかうら王 JupyterLab 機械学習環境構築サンプル

A local AI chatbot powered by Qwen2.5-1.5B, FastAPI, and Gradio. Includes document indexing with FAISS for RAG (Retrieval-Augmented Generation) and optional GPU acceleration (RTX 3060 optimized).