ArtificialGuyBR

Home / Blog / Training LoRAs

Training LoRAs

Dataset preparation, captioning, hyperparameters and the VRAM reality of training your own adapters.

26 articles

Automated LoRA Dataset Creation: Extract, Filter, Tag, QA

Build LoRA training sets from anime video and generative tools — automated extraction, tagging, and quality checks that keep the datas…

IPAdapter FaceID vs LoRA for Character Consistency

Compare IPAdapter FaceID with trained LoRAs for character identity across images, including seed/pose control and expression preservat…

FLUX Consistent Characters Without Training

How FLUX achieves consistent character generation without LoRA training via reference conditioning, Redux adapters, and seed disciplin…

FluxGym FLUX LoRA Training: Colab, RunPod, Hidden Settings

Guide to FluxGym FLUX LoRA training on Colab and RunPod — including the hidden Kohya settings every trainer should know.

Flux LoRA Training Tools Compared

Compare Civit Trainer, Kohya_ss, ai-toolkit, and fluxgym for training Flux LoRA models, with setup notes and source links.

How LoRAs Work and How to Use Them in Stable Diffusion

Understand LoRA mechanics: weight changes at inference, strength controls, stacking multiple adapters, matching base models, and prope…

LoRA Training Settings: What Works and What Doesn't

Which LoRA settings actually work, and how to test them yourself.

Finding and training male character LoRAs

Why male character LoRAs feel scarce on Civitai, what the verified training metadata and directories actually show.

Merging LoRAs vs Stacking

When to merge LoRAs into one adapter vs stacking them, the weight math, and the quality trade-offs.

Stable Diffusion Consistent Character Without LoRA

Prompt techniques for consistent SD characters without LoRA training.

LoRA Regularization Images: When to Use Them

Learn when regularization images help vs. waste compute in LoRA training, how to source them, and the kohya_ss folder conventions.

SDXL LoRA Training: Colab vs Hosted Trainers

Compare free T4 GPUs on Colab vs Kaggle for SDXL LoRA training, understand session timeouts, and discover hosted trainer alternatives.

SDXL LoRA Training Guide: Lessons from 10 Released Models

Expert SDXL LoRA training guide covering dataset choice, caption style, and hyperparameters from 10 photorealistic model creators.

Synthetic Faces: Training Sets and the Diversity Trap

How AI-generated portrait datasets enable consistent character training while avoiding real-person likeness issues — and the diversity…

Train LoRAs on Limited Hardware

Free Colab paths, AMD ROCm setups, and VRAM guidance for LoRA training.

Anima LoRA Training: Settings, Samplers, and Local Setup

How to configure Anima for image generation, pick the right sampler, and train a LoRA locally with verified settings and hyperparamete…

Captioning Tools 2026: JoyCaption vs WD Tagger vs Manual

Compare JoyCaption Beta One's 12 caption styles and word-count control against WD Tagger's ONNX batch inference, plus manual tagging w…

RunPod vs Vast.ai for LoRA Training on Rented GPUs

Choose the right cloud GPU instance, compare templates, and keep costs low.

Build a LoRA Dataset: Sources, Cleanup, Captioning Tools

A practical guide to sourcing images, cleaning data, and using JoyCaption and WD14 tagger for LoRA training dataset preparation.

LoRA Library: Folders, Previews, ComfyUI Manager & Kohya

Organize LoRA models with folder conventions, preview naming, and metadata. Set up ComfyUI Lora Manager and Kohya GUI.

Fixed-Seed Checkpoint and LoRA Comparison

A practical methodology for fair Stable Diffusion model comparisons — control variables and read grids honestly.

Textual Inversion Training Guide 2025: Embeddings vs LoRAs

When to use Textual Inversion over LoRA, Kohya_ss and A1111 settings, and the learning-rate gap explained.

Z-Image Turbo LoRA: Dataset, Precision, Adapter, AI Toolkit

Train Z-Image Turbo LoRAs with AI Toolkit: dataset sizing, fp8 quantization, training adapter, sigmoid timestep, and Flux/SDXL differe…

FLUX.1 LoRA Training Parameters: The Settings That Matter

FLUX.1 LoRA training parameters explained: dataset prep, captioning, learning rate, network dim and alpha, and VRAM for 12GB–24GB GPUs.

Train Your First LoRA Free: Data, Captions, Settings

Free LoRA training guide: dataset prep, WD14/BLIP captioning, and the hyperparameters that actually matter. Colab + local workflows.

JoyCaption, TagGUI, and AICaptionHelper

Compare three batch captioning tools for Stable Diffusion datasets

AI videoModels of 2026ComfyUIPrompting and controlFixing things

← All articles