KohakuBlueleaf/LyCORIS

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

2508 stars · 181 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

LyCORIS is a Python library implementing parameter-efficient fine-tuning algorithms (LoRA/LoCon, LoHa, LoKr, IA3, DyLoRA, and more) for Stable Diffusion and similar diffusion models. It provides training utilities and integrations with popular Stable Diffusion UIs for creating compact model adaptations.

Use cases

• train lora models for stable diffusion
• fine-tune stable diffusion with parameter-efficient methods
• create small adapter models for image generation
• compare loha vs lokr vs lora fine-tuning
• train stable diffusion adapters with limited gpu memory
• export lycoris models for use in a1111 webui

When to choose

• you need alternatives to plain LoRA such as LoHa, LoKr, or DyLoRA for diffusion model fine-tuning
• you want compact fine-tuned adapters for Stable Diffusion with trade-off control over fidelity and flexibility
• you are training Stable Diffusion adaptations and need PyPI-installable tooling with webui integration

When to avoid

• you need parameter-efficient fine-tuning for large language models rather than diffusion models
• you want full fine-tuning of all model weights without adapter methods
• you need a turnkey GUI training application rather than a library

Facets

library · maturity active

machine-learning llm-training sdk machine-learning image-processing deep-learning artificial-intelligence python cross-platform lora stable-diffusion parameter-efficient-fine-tuning loha lokr dylora diffusion-models peft gpu

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