🖥️AI-Toolkit
The ultimate training toolkit for finetuning diffusion models
⭐ Very popular: 12k stars, gaining about 78 a week
View on GitHub ↗repo profile
momentum
durability
since we covered it
why it's a big deal
- Consolidates finetuning for a wide range of diffusion models, covering image models like FLUX, SDXL, and Stable Diffusion 1.5 plus video models such as Wan and LTX-2, into one training suite.
- Targets consumer-grade hardware, so people without datacenter GPUs can train LoRA and LoKr adapters on their own machines.
- Offers both a CLI and a web UI for job management, which suits both scripted workflows and users who prefer not to run everything from the terminal.
under the hood
- Written mostly in Python with a TypeScript web interface that runs on Node.js at port 8675, with optional auth via the AI_TOOLKIT_AUTH environment variable.
- Jobs are defined in YAML configs copied from config/examples and run with python run.py, producing timestamped output folders that store checkpoints and resume training after interruption.
- Supports LoRA and LoKr training with configurable rank, alpha, and factor, plus layer-specific targeting through only_if_contains and ignore_if_contains network parameters.
Radar summary, generated from the project's public sources
star history
- PR#15 6k 2025-08-20
- now 12k + 6k since first covered
curve is sampled from GitHub's star history, plus our own daily readings since we covered it; the dashed stretch is before we first covered it, the solid line since. figures at coverage are the numbers we printed then (approx.), current count is live.
understory
Quietly building: more output than attention, for now.
- output, commits & releases
- clout, star velocity
output = commits & releases; clout = star velocity, both 0 to 100 monthly indices; the gap where output runs above clout is the understory. The understory →
covered in
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Diffusion Model Finetuning Suite
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