This model is a precision-tuned ZiT merge designed to push the boundaries of fine-grained texture, anatomical accuracy, and atmospheric lighting while maintaining compatibility with LoRAs trained on the base models. I've train my character and style LoRAs on vanilla Z-Image Base. They work fine on Turbo derived models and tend to be more stable during training.I will upload future models to Hugging Face also, it's a lot faster than dealing with a VPN<a target="_blank" rel="ugc" href="https://huggingface.co/PsychoLogic/PsychoMix_ZiT">https://huggingface.co/PsychoLogic/PsychoMix_ZiT</a><h2 id="the-composition">The Composition</h2>The architecture of this model is a blend of checkpoints and custom refinements:<h2 id="v1.x">v1.x</h2>Core Foundation based on Moody Porn Mix v10 for subject pose, with various other models merged for style and consistency (see 'About this version' for specifics for a particular release)For a more raw/realistic look I recommend using z-image-turbo-flow-dpo with a strength of -0.5 to -0.75 (yes, negative). It was baked into the base model and many (myself included) think it's merely a slopifier.<h2 id="v2.x">v2.x</h2><ul><li>Core Foundation: A balanced merge of Z-Image Turbo NSFW v7.2 for subject pose, CyberRealistic Z-Image Turbo Catalyst v0.7 for style and technical precision, and selective merge from Famegrid ZIB v1.0, focused on later layers</li></ul><h3 id="feedback-and-&quot;show-your-work&quot;">Feedback &amp; "Show Your Work"</h3>I am actively looking for constructive feedback to improve this and other models. If the model isn't performing as expected for you, please help me fix it!The "Pics or it didn't happen" Rule: If you encounter issues (artifacts, anatomy failures, or poor prompt adherence), please post your generation with metadata (Seed, Prompt, Sampler). Negative comments without an image and settings typically don't help. If you want a fix, show the failure so I can tune it out in the next merge.

PsychoMix ZiT

Second attempt at reducing the Asian bias from the base model. I feel like I nailed it this time. SFW gens of male subjects are working well, and it isn't feminizing my SelfAI shots.I re-balanced the HFP dataset to 50/50 male/female subjects, and used this to make a ZiB LoRA to apply to Moody and Dark Beast before merging them in. It's only 5000 steps in at this point but the first test run was too good so I decided to cut v1.1 using it now.I've been training my character and style LoRAs on vanilla Z-Image Base. They work fine on Turbo derived models, don't listen to any ignoramus who tells you otherwise.(v1.1) FP16 Compatibility Fix (for non-NVIDIA &amp; ComfyUI users)I am uploading a new 'fp16' variant of the v1.1.0 model to resolve the "Black Output / NaN in Latent" issue reported, particularly those using SD-WebUI-Forge or non-BF16 LoRAs. Note the weights are still in BF16 but will no longer produce NaNs when dumbly cast to FP16 by dodgy inference pipelines.What happened: During the merge process for this model, a single attention layer developed weight outliers (values exceeding 65,504). While these weights technically function in BF16 (used by ComfyUI on my NVIDIA hardware), they exceed the numerical range of FP16, which is the standard precision used by some hardware and inference implementations (Forge Neo). When these engines encountered those extreme values, they would overflow into Infinity/NaN, resulting in black images. The fixed version clamps these outliers to a safe range of [-60,000, 60,000], ensuring compatibility across all platforms.fp8 quant for this version has been added. This was made using <a target="_blank" rel="ugc" href="https://github.com/silveroxides/convert_to_quant">https://github.com/silveroxides/convert_to_quant</a>, <code>convert_to_quant -i PsychoMix-ZiT_v1.1.0.safetensors --simple --comfy_quant --device cuda --manual_seed 42</code> . Note it produces different results to the bf16 model and seems less stable. I tried also without the <code>--simple</code>, it took longer and produced similar a result which failed to render the shadows correctly in the 'girl at blinds' image.Still working on GGUF quants, should be a matter of days. Would be quicker if I didn't have to upload my free content via a VPN because CivitAI don't deem the Australian market to be worth the investment.

Files with SHA256: 69e95303a0fa5024a33cac5c68494f3533a6bb9afb6b6929e8f06c30d8c08f50