Lora Dataset Studio – End‑to‑End LoRA Pipeline
Use Lora Dataset Studio to build, curate, train, and export LoRA models with auto‑framing and cloud training.
Integrate Lora Dataset Studio into your pipeline to automate dataset creation and training.
Summary
Lora Dataset Studio is a comprehensive open‑source pipeline for building, curating, training, testing, and exporting LoRA models, available on GitHub (https://github.com/perfectgf/lora-dataset-studio). The Build stage offers three dataset types (character, concept, style) and three image sources (reference photo, import, web scrape), with a guided workspace that unlocks steps as prerequisites are met and allows in‑place prompt editing and regeneration. Curate & caption includes auto‑framing + meter scoring, face‑similarity scoring with InsightFace, model‑matched captions via JoyCaption or Ollama, and watermark cleanup using Clean or LaMa. Train provides no‑hand‑tune training with adaptive steps, a GPU queue, auto rembg masks, and supports five model families (Z‑Image, SDXL, Krea 2, FLUX.1, FLUX.2) with preset recipes and cloud training via vast.ai. Test & ship includes a Test Studio grid‑test for checkpoint ranking and an export ZIP that pairs images with captions for any AI toolkit. Comfort & access features phone access via QR, a setup wizard, and a diagnostics report. The tool is designed to streamline LoRA workflows for artists and developers, reducing manual configuration and enabling rapid iteration.
Key changes
- Offers three dataset types (character, concept, style) with auto‑framing + meter scoring
- Includes face‑similarity scoring via InsightFace and model‑matched captions using JoyCaption/Ollama
- Provides no‑hand‑tune training with adaptive steps, GPU queue, auto rembg masks, and supports five model families
- Supports cloud training via vast.ai and a runs hub for local and cloud runs
- Test Studio grid‑test for checkpoint ranking and export ZIP with image‑caption pairs
- Phone access via QR, setup wizard, and diagnostics report