Indian Matchbox Art Style: Text-to-Image Generator

Two style LoRAs that generate new vintage Indian matchbox labels from a text prompt. Both were trained on the same 197 labels (spearb0lt/Indian-Matchbox-Labels) with the trigger word phlmx:

Each folder also has CARD.json: every setting and measured number of its training run. The training notebooks, with all their outputs, are on GitHub: spearb0lt/Indian-Matchbox-Art-Style-Text-to-Image-Generator.

Samples

SD3.5-medium LoRA

SDXL LoRA

The peacock (MAYUR) and the swan in this gallery come from an earlier SDXL LoRA run of notebook 55 that was trained on Cooper Hewitt museum prints, whose weights are not published; the other eight images come from the published SDXL LoRA. Each image's run is recorded in images/image_prompts.json.

Every prompt, seed and setting is in images/image_prompts.json.

Which one to use

Left: SDXL LoRA. Right: SD3.5-medium LoRA. Same subject and headline, each with its own notebook's settings. The SDXL peacock comes from the earlier SDXL run of notebook 55 (trained on museum prints, weights not published, seed 478163327 at strength 0.8). More pairs are in images/compare/.

• SD3.5-medium LoRA: headlines are usually spelled correctly, with flat, saturated colour and clean outlines. Best for legible, bold labels.
• SDXL LoRA: a muted palette with ink-on-paper texture and engraved line work, like a worn original; headlines are often misspelled. Works in the widest range of tools (kohya file).

Part of the difference in look comes from the base models: with the LoRA switched off (scale 0.0), base SD3.5-medium already draws flat, saturated colour and base SDXL a softer, painted picture; on a short headline such as MAYUR both base models are roughly right. SD3.5 also has a T5-XXL text encoder and joint text-image attention, and its LoRA was trained on hand-written captions that spell out each label's headline. The GitHub README has the full comparison.

Model details

Base models

Parameter counts are read from each repository's safetensors files.

The LoRA adapters in this repository

Usage

import torch
from diffusers import StableDiffusionXLPipeline, StableDiffusion3Pipeline, AutoencoderKL

REPO = "spearb0lt/Indian-Matchbox-Art-Style-Text-to-Image-Generator"
NEG = "photograph, photorealistic, 3d render, blurry, low quality, watermark"

# SDXL LoRA
vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
sdxl = StableDiffusionXLPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", vae=vae,
                                                 torch_dtype=torch.float16, variant="fp16").to("cuda")
sdxl.load_lora_weights(REPO, subfolder="sdxl", weight_name="phlmx_style_sdxl_ep10_diffusers.safetensors")
img = sdxl("phlmx, a matchbox, a white swan swimming in front of a red sunburst, yellow background, "
           "headline 'SWAN BRAND'", negative_prompt=NEG, width=1152, height=896,
           num_inference_steps=30, guidance_scale=6.0).images[0]

# SD3.5-medium LoRA (accept the base model's licence on the Hub first)
sd3 = StableDiffusion3Pipeline.from_pretrained("stabilityai/stable-diffusion-3.5-medium",
                                               torch_dtype=torch.bfloat16).to("cuda")
sd3.load_lora_weights(REPO, subfolder="sd3.5-medium", weight_name="pytorch_lora_weights.safetensors")
img = sd3("phlmx, a matchbox label, a roaring tiger's head inside a yellow circle, red background, "
          "headline 'TIGER'", negative_prompt=NEG, width=768, height=1152, num_inference_steps=28,
          guidance_scale=5.0, joint_attention_kwargs={"scale": 0.9}).images[0]

Prompts. Start with the trigger and follow the shape of the training captions: phlmx, a matchbox label, <what is shown>, <background colour>, headline '<one or two words>'. Short English headlines render best. Style words such as "vintage" are not needed.

Settings used for the samples. SDXL: LoRA scale 1.0, 30 steps, CFG 6.0, sizes of about 1 megapixel (832 x 1216, 1216 x 832, 1024 x 1024 and similar). SD3.5-medium: LoRA scale 0.9, 28 steps, CFG 5.0, 768 x 1152 or 1152 x 768.

ComfyUI / AUTOMATIC1111: use sdxl/phlmx_style_sdxl_ep10_kohya.safetensors with SDXL 1.0 at weight 1.0.

Training

Measured on held-out evaluation prompts (each column on its own prompts, so not comparable across columns):

Limitations

• Lettering. Small secondary text is usually invented pseudo-text; the SDXL LoRA also misspells many headlines. Indian scripts (Devanagari, Tamil and others) are not rendered as real words by either model.
• The trigger can leak into the image. The word phlmx sometimes appears printed on the label.
• The SDXL captions. Many of its auto-captions were longer than SDXL's 77-token limit, and some kept <pad> tokens, which weakened what it learned about lettering (documented in the notebook, §5.2).
• Narrow domain. Trained only on matchbox labels; other subjects come out as matchbox labels.

Licence

• The SDXL LoRA is a derivative of SDXL 1.0 and follows the CreativeML Open RAIL++-M licence.
• The SD3.5-medium LoRA is a derivative of SD3.5-medium and falls under the Stability AI Community License.
• The training images are historical commercial prints of mixed provenance whose rights are not cleared (see the dataset card). The LoRAs are shared for research and education.

Credits

The project started from a Reddit post about a "desi-max" style LoRA trained on Qwen-Image (yenupam/desi-max). Its data was not published; these LoRAs use their own data and smaller base models.