[F2K]Image Repair - v1.0 rank16

[F2K]Image Repair

LORA
Reprint


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[F2K]Image Repair by user_z on Tensor.Art

Version Detail

FLUX_2_KLEIN_9B_BASE
https://civitai.com/models/2432353/image-repair-flux2-klein9b?modelVersionId=2734929 LoRA Weight: 1.0 Trigger Words: make image high quality CFG: 1 Steps: 4-6 Fixed the issue, now it works with gguf models too Image Repair Flux.2-Klein9B Hey everyone! This is my second LoRa. So, I took the original idea from Link How it works: I trained this using a LoRA subtraction method (clean originals vs. degraded/pixelated versions). Because it extracts the exact "delta" of the degradation, it only targets the artifacts and noise without altering the core of image. It may not work with all images, on very complex detailed patterns it can hallucinate like the original flux2, try a different seed. Also, as you can see from the examples, the original flux2 saturation is poorly controlled. Training details: Latent: 512X512 (Also lora work with higher resolution and other aspect ratio) I tried 1024 latent size when training, but OOM forced me to optimize the settings. Lora rank: 16 Steps: 2000 Grad_accum: 4 Source images: 227 (all created in 2k/4k NanoBananaPro + Some Flux2.Kein9B) These settings were before lora was weakened. She was initially retrained. this is 0.3 Strength of original train. As with the author of the idea, all settings were created by a neural network (not chatgpt) and Python scripts were used for configuration. Recommended Settings: LoRA Weight: 1.0 Trigger Words: make image high quality CFG: 1 Steps: 4-6 I hope for positive feedback, but I hope you find this version useful. Also think it can be improved further. Later, soon... Do not use lora with the ImageScaleToTotalPixels node. Some image with this node is totally sh*t

Project Permissions

Model reprinted from : https://civitai.com/models/2432353/image-repair-flux2-klein9b

Reprinted models are for communication and learning purposes only, not for commercial use. Original authors can contact us to transfer the models through our Discord channel --- #claim-models.

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