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MicksHF/fusal-refchar-v17-stage2-3
fusal-refchar-v17-stage2-3 is a machine learning model from MicksHF. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This repository contains the Stage2 and Stage3 DoRA checkpoints for the fusal-refchar-v17 reference-character edit training run.
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Updated Jul 7, 2026
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From the Hugging Face model README
This repository contains the Stage2 and Stage3 DoRA checkpoints for the
fusal-refchar-v17 reference-character edit training run.
Use the final Stage3 checkpoint for high-resolution testing:
stage3/refchar_v20_stage3_dora64_960_bf16_96gb.safetensors
Stage2 is included so the training trajectory can be reproduced and compared:
stage2/refchar_v20_stage2_dora64_768_bf16_96gb.safetensors
stage2/: Stage2 DoRA checkpoints, including final and retained late checkpoints.stage3/: Stage3 DoRA checkpoints, including final and retained late checkpoints.configs/: AI Toolkit configs used for the run and smoke test.logs/: training logs for Stage2 and Stage3.samples/: generated sample images and Stage3 trajectory comparison images.docs/: training notes, file manifest, and SHA256 checksums.Base model:
Qwen/Qwen-Image-Edit-2511Dataset:
YuHuison/fusal-refchar-v20Network:
to_q, to_k, to_v, to_out,
add_q_proj, add_k_proj, add_v_proj, to_add_outStage2:
76810000adamw8bit1e-4flowmatchweighted0.05768x768, every 500 stepsStage3:
9601280x720, every 1000 steps10000adamw8bit3e-5flowmatchweighted0.05For 16:9 images, AI Toolkit resolution 960 maps to the 1280x720 bucket.
The training run did not use negative prompts. For this diffusion training setup, the model learns from the reference image and positive edit caption condition. Negative prompts are mainly an inference-time steering tool, not a required training field.
See docs/TRAINING_NOTES.md for the trajectory notes and operational details.