single-gpu

Run a documented subset of verl-style OPD on one consumer GPU—typed config, Parquet prompts, and PEFT scale-out artifacts.

Non-intimidating guide to create a KVM GPU Passthrough via libvirt/virt-manager on systems with only one GPU.

Train Dense Passage Retriever (DPR) with a single GPU

Seamless NVIDIA GPU hot handoff between Proxmox host and VM — bind/unbind nvidia ⇆ vfio-pci safely, no reboots.

A no-code browser-based tool that enables domain experts to fine-tune AI language models using their own knowledge with nothing more than a CSV file.

🚀 Achieve rapid training of NanoGPT (GPT-2 124M) on a single RTX 4090, targeting a validation loss below 3.28 with FineWeb-Edu data.

Cog Single GPU Quantized Implementation of Step-Video-T2V

GPT-2-class language models trained from scratch in PyTorch on one RTX 3090, with 10B-token data curation and full GPT-2 comparisons.

🔌 单卡 GPU LLM 推理网关 · 模型即插件 · 三态 GPU · 9 云端预设 · macOS Dashboard

Autonomous research stack for continuously improving LLM training through automated experimentation. Single-GPU research labs. Karpathy-inspired.

🧠 Minimal, hackable Group Relative Policy Optimization (GRPO) for LLM alignment — the algorithm behind DeepSeek-R1. Train reasoning models on a single GPU.

A lightweight, end-to-end implementation of Stable Diffusion built from first principles on a single T4 GPU. Features a custom 192-channel U-Net, VAE, and a CLIP encoder, optimized for consumer hardware and trained on approx. 168k images.

A reproducible, memory-efficient pipeline for training a 1.2B-parameter bilingual Chinese-English GPT language model from scratch on a single RTX 4090. 一个可复现且显存高效的训练管线，用于在单张 RTX 4090 上从零训练 12 亿参数的中英双语 GPT 语言模型。

AI agents running research on single-GPU nanochat training automatically

Whole slide training with single GPU

Neurosymbolic AI organism built from scratch on a single GTX 1080: latent-space reasoning, frozen growth stages, knowledge as graph edges, automated hypothesis discovery. 15 months of honest pre-registered research journals (RU).

GitHub template for reproducible single-GPU ML experiments - config-driven training, multi-seed evals, VRAM budgeting.

Hybrid LLM pre-training framework fusing Multi-Head Latent Attention, Gated Delta Net, DeepSeek MoE, and Multi-Token Prediction — 415M active params, 8.31B tokens, single A100 80GB.