The most efficient one-page LoRA trainer for Anima 2B. Optimized for 6GB+ VRAM, featuring a smart dataset analyzer and real-time previews.
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Updated
May 31, 2026 - Python
The most efficient one-page LoRA trainer for Anima 2B. Optimized for 6GB+ VRAM, featuring a smart dataset analyzer and real-time previews.
One-click Windows installer for Z-Image Turbo AI image generation. Optimized for low-VRAM GPUs (4GB+). Features Gradio web UI, automatic setup, and GGUF model support.
Hierarchical RAG architecture scaling to 693K chunks on consumer hardware (4GB VRAM). Features 3-address routing, hybrid vector+graph fusion, and SetFit classification.
"Adaptive Hybrid Quantization Framework for deploying 7B+ LLMs on low-VRAM devices (e.g., GTX 1050). Features surgical block alignment and Numba-accelerated inference.
Taiwanese Hokkien (Taigi) speech-to-text transcriber - MediaTek Breeze-ASR-26 with faster-whisper, tuned for RTX 3050 4GB low-VRAM GPUs. Gradio UI, CLI, Docker, SRT/VTT/TXT/JSON.
Lightweight 6GB VRAM Gradio web app with auto-installer for running AuraFlow locally — no cloud, no clutter.
Simple FP16 image upscaler for all GPUs (low-mid end users)
Perkunas AI Training Platform is a memory-aware model training and serving system for serious language model experimentation under tight hardware limits. It combines streaming training, rich telemetry, guarded recovery, checkpoint export, and OpenAI-compatible serving.
A workbench for running large Mixture-of-Experts LLMs locally on consumer hardware with a tight VRAM budget.
A privacy-first Generative AI pipeline for prototyping 3D-style game assets on consumer hardware. Optimized for low-VRAM (4GB) GPUs using PyTorch, Diffusers, and Streamlit.
Unofficial AMD ROCm low-VRAM fork of Hunyuan3D-2.1 — 6-view PBR texture at ~10.5 GB peak on 20 GB AMD. See README_AMD_ROCM.md.
Пайплайн для эффективного 4-битного (QLoRA) дообучения Qwen3-8B на потребительских видеокартах (10 ГБ VRAM). Включает этап SFT и этапы сбора данных.
Lightweight Stable Diffusion engine with plugin-based pipelines, VRAM-safe execution, and full 4GB GPU support.
A production-ready, frugal, sovereign AI system that orchestrates India's open-source language models to achieve state-of-the-art reasoning on consumer hardware through Test-Time Compute (TTC) and Cognitive Serialization.
Automated video inpainting pipeline for ComfyUI, built for long sequences under tight VRAM limits. Combines chunked processing, dynamic Qwen-VL detection and a patched bidirectional SAM2 tracker with Wan 2.1 VACE — runs on a 16GB laptop GPU.
Lightweight SDXL LoRA trainer optimized for 8GB VRAM GPUs. GUI with training, auto-captioning (Ollama) and image search (SearXNG).
LoRA fine-tuning for diffusion models on constrained hardware — VRAM budget estimator, reproducible configs and dataset tooling for 8 GB CUDA GPUs and Apple Silicon
ComfyUI nodes for Ideogram GGUF inference on 8GB VRAM.
Run Stable Diffusion locally on Intel iGPU/CPU with OpenVINO acceleration. Uncensored, Low VRAM, No NVIDIA required!
Veizik — hardware-aware local AI media runtime. Hardware detection, low-memory execution planning, local licensing and experimental AI-video rendering.
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