---
license: apache-2.0
base_model: Qwen/Qwen-Image-2512
tags:
  - diffusers
  - diffsynth
  - controlnet
  - text-to-image
  - cyrillic
---

# Qwen-Image Cyrillic Blockwise ControlNet

Blockwise Canny ControlNet checkpoint fine-tuned for copying real Cyrillic glyph controls
into Qwen-Image output. It starts from
`DiffSynth-Studio/Qwen-Image-Blockwise-ControlNet-Canny` and keeps the DiffSynth checkpoint
key layout.

## Artifact

- `model.safetensors`
- 2,266,838,080 bytes
- SHA-256: `8f7ed8860b94283d48b72859cb7ec715a6da7ae522a4a312004e635abfc8f9cb`

## Training

- base: `Qwen/Qwen-Image-2512`
- trainable module: full `blockwise_controlnet`
- 128 prepared edge-control samples at 512×512
- 128 steps
- learning rate: `1e-5`
- trainable precision: BF16
- frozen transformer, text encoder, and VAE storage/onload: FP8
- gradient checkpointing enabled

Exact hashes and arguments are in the separate configuration repository.

## Validation

Fixed held-out benchmark: 100 unseen Russian words, 512×512, 20 steps, seed 3000 plus sample
index, fitted edge control, scale 0.85.

- manual exact Cyrillic score: 99/100
- OCR diagnostic exact: 77/100
- mean OCR CER: 0.1142
- mean glyph similarity: 0.9564

The single manual failure was `ЕЩЁ → ЁЩЁ`. Edge scale retries 0.9, 1.0, and 1.1 and a
filled-control retry at 0.7 with the same seed did not correct it. OCR is diagnostic only;
the reported 99/100 score comes from manual inspection of all five contact sheets.

## Limitations

Training data uses a narrow synthetic typography distribution: simple backgrounds, limited
fonts, and isolated words. This checkpoint is intended for glyph-guided generation, not
unguided spelling, paragraphs, arbitrary layouts, handwriting, or guaranteed OCR-perfect
output.