Qwen-Image-Cyrillic-ControlNet

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.