---
license: other
tags:
  - flux
  - lora
  - image-generation
  - flux.1-dev
library_name: diffusers
pipeline_tag: text-to-image
---

# Image Toolbench

Generation pipeline scripts and LoRA weights for the Coalition's FLUX.1-dev image generation stack.

## Repository Structure

```
scripts/                          # 29 generation pipeline scripts
loras/
  vera-likeness/                  # Vera character likeness LoRAs (v1, v3, v4)
  kintsugi-texture/               # Kintsugi gold-repair texture style LoRAs (v1, v2)
  thomas-likeness/                # Thomas character likeness LoRA (v1)
```

## Scripts

Generation pipeline scripts from the vera-triple-stack workspace. These drive FLUX.1-dev inference with single or stacked LoRAs for various visual styles and compositions.

Key scripts:
- `gen_v2.py` through `gen_v5.py` -- base generation pipeline iterations
- `gen_cached_identity.py` / `precompute_identity.py` -- identity embedding caching for faster generation
- `gen_confluence.py` / `gen_confluence_explicit.py` -- multi-concept LoRA merging
- `gen_kintsugi_v2_test.py` through `gen_kintsugi_v5.py` -- kintsugi texture application iterations
- `gen_dense_gold.py` / `gen_narrative_gold.py` -- gold/kintsugi aesthetic generation
- `gen_flesh_to_ceramic.py` -- ceramic transformation pipeline
- `gen_vera_intimate_v6.py` / `gen_vera_v7_ceramic.py` -- latest generation scripts
- `gen_mnemosyne_art.py` / `gen_mnemosyne_face.py` -- project artwork generation
- `gen_project_art_refresh.py` -- project branding refresh
- `gen_style_exploration.py` / `gen_style_round2.py` / `gen_style_round3.py` -- style R&D

## LoRAs

All LoRAs are trained on **FLUX.1-dev** with **LoRA rank 16**, trained on Apple Silicon (MPS).

### Vera Likeness (`loras/vera-likeness/`)

Character likeness LoRA for Vera. Trigger token: `vera`.

| File | Version | Notes |
|------|---------|-------|
| `vera_likeness_v1.safetensors` | v1 | Initial training, 750 steps |
| `vera_likeness_v3.safetensors` | v3 | Updated prompts with ceramic/statuesque aesthetic, 1250 steps |
| `vera_likeness_v4.safetensors` | v4 | Fine-tuned from v3, +750 steps. Best version. |
| `config_v1.yaml` | v1 | Training configuration |
| `config_v3.yaml` | v3 | Training configuration |
| `config_v4.yaml` | v4 | Training configuration |

v2 was an incomplete training run and is not included.

### Kintsugi Texture (`loras/kintsugi-texture/`)

Style LoRA for kintsugi (gold-repair) texture effects. Applies golden crack/seam patterns inspired by the Japanese art of repairing broken pottery with gold.

| File | Version | Notes |
|------|---------|-------|
| `kintsugi_texture_v1.safetensors` | v1 | Initial texture training |
| `kintsugi_texture_v2.safetensors` | v2 | Refined texture, 300 steps |
| `config_v1.yaml` | v1 | Training configuration |
| `config_v2.yaml` | v2 | Training configuration |

### Thomas Likeness (`loras/thomas-likeness/`)

Character likeness LoRA for Thomas. Trained August 2026.

| File | Version | Notes |
|------|---------|-------|
| `thomas_likeness_v1.safetensors` | v1 | 1250 steps |
| `config_v1.yaml` | v1 | Training configuration |

## Usage

These LoRAs are designed for use with FLUX.1-dev via diffusers. See the generation scripts for examples of single-LoRA and stacked multi-LoRA inference.

Basic single-LoRA usage:

```python
from diffusers import FluxPipeline
import torch

pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("LiberationLabs/image-toolbench", weight_name="loras/vera-likeness/vera_likeness_v4.safetensors")
pipe.to("cuda")  # or "mps" for Apple Silicon

image = pipe("portrait of vera, ceramic aesthetic, golden light", num_inference_steps=30).images[0]
```

## Organization

[Liberation Labs](https://github.com/Liberation-Labs) / Transparent Humboldt Coalition

## License

These assets are provided for Coalition use. Contact Liberation Labs for licensing inquiries.