
GENOVA APEX is an experimental model.
I created by merging my previous Gene Quantum model https://civitai.com/models/885573/flux-gene-beauty with DEDISTILLED models and my own trained LoRAs. The process involved multiple stages and is purely an experiment to achieve high detail and realism similar to DEDISTILLED in just 8 generation steps(+ 8 generation steps Hires. Fix) .
Version (UNet) – This version requires Flux VAE, Clip-L, and T5XXL to work effectively with the Flux development model.
Recommended Settings for Optimal Generation
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Sampling Method and Schedule Type: Euler Beta
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Sampling Steps: 8 steps
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I use Hires. Fix because it provides significantly better results: 8 steps, upscale 1.2.
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My configuration: RAM 64Gb, VRAM 16Gb
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Workflow for ComfyUi:
I use a straightforward workflow for image generation, available here: Flux Photos DEV Workflow-
HyperDetailer workflow FLUX PHOTOS DEV (HyperDetailer update) https://civitai.com/models/670083
However, it requires a lot of memory because the process includes nodes for detail enhancement and upscaling, which also deliver the best results.
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Please note that the quality on Forge may be lower than on ComfyUI. Here are the parameters I used: last update Forge, steps 8, euler beta, Distilled CFG Scale 3.5, CFG Scale 1 and I recommend use Hires.Fix Upscaler Latent or other be better, 8 steps, Upscale by 1,2 (higher upscale factors give better results but are slower and require more VRAM/RAM), Denoising strength 0,7, Distilled CFG Scale 3.5, CFG Scale 1 .
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My Prompt Writing Assistant: https://civitai.com/articles/7868/gpts-flux-photo-prompt-gen
P.S. The results I observe during the modeling process are even better than those I obtain from the final output of this process. Therefore, I continue experimenting, as the reason for this discrepancy has not yet been found...
描述:
This model prioritizes realistic images.
训练词语:
名称: genovaAPEX_real.safetensors
大小 (KB): 11622613
类型: Model
Pickle 扫描结果: Success
Pickle 扫描信息: No Pickle imports
病毒扫描结果: Success