{"adoption": {"forks": 132, "observed_at": "2026-08-28T04:04:19.074319+00:00", "stars": 1307}, "canonical_url": "https://ross.abutalabs.com/products/lora_easy_training_scripts", "card": {"archived": false, "artifact_type": "application", "description": "A UI made in Pyside6 to make training LoRA/LoCon and other LoRA type models in sd-scripts easy", "domain": ["machine-learning", "image-processing", "artificial-intelligence", "developer-tools"], "enriched": true, "function": ["machine-learning", "llm-training", "gui", "gpu-computing"], "health_score": 36, "homepage": null, "language": "Python", "license": "GPL-3.0", "license_family": "copyleft", "maturity": "active", "member_repos": ["derrian-distro/LoRA_Easy_Training_Scripts"], "name": "derrian-distro/LoRA_Easy_Training_Scripts", "platform": ["windows", "python"], "pushed_at": "2025-06-05T23:45:38+00:00", "repo": "derrian-distro/LoRA_Easy_Training_Scripts", "stars": 1307, "tags": ["lora-training", "stable-diffusion", "pyside6", "sd-scripts", "fine-tuning", "lycoris", "dreambooth", "linux", "gpu", "desktop"], "topics": [], "urls": [], "use_cases": ["train a lora for stable diffusion without writing scripts", "easy gui for kohya sd-scripts lora training", "fine-tune stable diffusion models on my own images", "train locon or lycoris adapters", "train loras on google colab without a gpu", "simplify lora training configuration"], "what_it_is": "A PySide6 desktop GUI that wraps Kohya's sd-scripts to simplify training LoRA, LoCon, and other LoRA-type models for Stable Diffusion. It streamlines configuration and execution of fine-tuning runs on Windows and Linux, with a Google Colab option for users without local GPUs.", "when_to_avoid": ["you need training methods beyond LoRA-family adapters (e.g., full fine-tunes or textual inversion)", "you prefer headless/CLI-only training pipelines or CI automation", "you need macOS support, which is not covered by the installers"], "when_to_choose": ["you want a GUI instead of editing config files or CLI scripts for LoRA training", "you train LoRA/LoCon/LoCR-style adapters for Stable Diffusion on Windows or Linux", "you lack a local GPU and want a ready-made Colab workflow"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/lora_easy_training_scripts", "repo": "derrian-distro/LoRA_Easy_Training_Scripts", "role": "main", "score": 33}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:04:19.074319+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T04:50:08.626676+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "751b3222f353d92c8ec7024d8da6eef964bff19a6190318039a8a843bd819182", "fetched_at": "2026-08-28T04:04:19.074319+00:00", "kind": "readme", "missing": false, "url": "https://github.com/derrian-distro/LoRA_Easy_Training_Scripts"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:04:19.074319+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T04:50:08.626676+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "751b3222f353d92c8ec7024d8da6eef964bff19a6190318039a8a843bd819182", "fetched_at": "2026-08-28T04:04:19.074319+00:00", "kind": "readme", "missing": false, "url": "https://github.com/derrian-distro/LoRA_Easy_Training_Scripts"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T04:50:08.626676+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "751b3222f353d92c8ec7024d8da6eef964bff19a6190318039a8a843bd819182", "fetched_at": "2026-08-28T04:04:19.074319+00:00", "kind": "readme", "missing": false, "url": "https://github.com/derrian-distro/LoRA_Easy_Training_Scripts"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:04:19.074319+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:04:19.074319+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:04:19.074319+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T04:50:08.626676+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "751b3222f353d92c8ec7024d8da6eef964bff19a6190318039a8a843bd819182", "fetched_at": "2026-08-28T04:04:19.074319+00:00", "kind": "readme", "missing": false, "url": "https://github.com/derrian-distro/LoRA_Easy_Training_Scripts"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:04:19.074319+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:04:19.074319+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T04:50:08.626676+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "751b3222f353d92c8ec7024d8da6eef964bff19a6190318039a8a843bd819182", "fetched_at": "2026-08-28T04:04:19.074319+00:00", "kind": "readme", "missing": false, "url": "https://github.com/derrian-distro/LoRA_Easy_Training_Scripts"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:04:19.074319+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:04:19.074319+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:04:19.074319+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T04:50:08.626676+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "751b3222f353d92c8ec7024d8da6eef964bff19a6190318039a8a843bd819182", "fetched_at": "2026-08-28T04:04:19.074319+00:00", "kind": "readme", "missing": false, "url": "https://github.com/derrian-distro/LoRA_Easy_Training_Scripts"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:04:19.074319+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:04:19.074319+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T04:50:08.626676+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "751b3222f353d92c8ec7024d8da6eef964bff19a6190318039a8a843bd819182", "fetched_at": "2026-08-28T04:04:19.074319+00:00", "kind": "readme", "missing": false, "url": "https://github.com/derrian-distro/LoRA_Easy_Training_Scripts"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T04:50:08.626676+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "751b3222f353d92c8ec7024d8da6eef964bff19a6190318039a8a843bd819182", "fetched_at": "2026-08-28T04:04:19.074319+00:00", "kind": "readme", "missing": false, "url": "https://github.com/derrian-distro/LoRA_Easy_Training_Scripts"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T04:50:08.626676+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "751b3222f353d92c8ec7024d8da6eef964bff19a6190318039a8a843bd819182", "fetched_at": "2026-08-28T04:04:19.074319+00:00", "kind": "readme", "missing": false, "url": "https://github.com/derrian-distro/LoRA_Easy_Training_Scripts"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T04:50:08.626676+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "751b3222f353d92c8ec7024d8da6eef964bff19a6190318039a8a843bd819182", "fetched_at": "2026-08-28T04:04:19.074319+00:00", "kind": "readme", "missing": false, "url": "https://github.com/derrian-distro/LoRA_Easy_Training_Scripts"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 25, "longevity": 94, "rhythm": 8}, "computed_at": "2026-09-03T02:20:16.233290+00:00", "flags": [], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 1329, "days_push": 454, "days_rel": null, "gap_med": null, "n_releases_24m": 0}, "score": 33, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}