--- license: other license_name: fair-ai-public-license-1.0-sd license_link: https://freedevproject.org/faipl-1.0-sd/ language: - en pipeline_tag: text-to-image tags: - safetensors - diffusers - stable-diffusion - stable-diffusion-xl - art library_name: diffusers --- # NoobAI-XL-Merges Various merges built on [Laxhar Lab's](https://huggingface.co./Laxhar) Illustrious-xl-based text to image model, uploaded for testing purposes. These are provided as-is, and YMMV. The user is responsible for any outputs produced using these checkpoints. Other models involved in these merges include: - [comin/IterComp](https://huggingface.co./comin/IterComp) - [CyberRealistic XL](https://civitai.com/models/312530/cyberrealistic-xl) ## Methods Perpendicular merges are done via [sd-mecha](https://github.com/ljleb/sd-mecha) using the Python API, for example:
1) Merge noobaiXLNAIXL_vPred10Version-cyberrealistic4-perpendicular ```python import sd_mecha sd_mecha.set_log_level() text_encoder_recipe = sd_mecha.model("noobaiXLNAIXL_vPred10Version.safetensors", "sdxl") unet_recipe = sd_mecha.add_perpendicular( sd_mecha.model("noobaiXLNAIXL_vPred10Version.safetensors", "sdxl"), sd_mecha.model("cyberrealisticXL_v4.safetensors", "sdxl"), sd_mecha.model("sd_xl_base_1.0_0.9vae.safetensors", "sdxl"), ) recipe = sd_mecha.weighted_sum( text_encoder_recipe, unet_recipe, alpha=( sd_mecha.blocks("sdxl", "txt") | sd_mecha.blocks("sdxl", "txt2") | sd_mecha.default("sdxl", "unet", 1) ), ) merger = sd_mecha.RecipeMerger( models_dir=r"C:\path\to\models\directory", ) merger.merge_and_save(recipe, output="output.safetensors") ```

2) Add v_pred and ztsnr keys to the resulting model for autodetection in Comfy/Forge ```python from safetensors.torch import load_file, save_file import torch state_dict = load_file("output.safetensors") state_dict["v_pred"] = torch.tensor([]) state_dict["ztsnr"] = torch.tensor([]) save_file(state_dict, "noobaiXLNAIXL_vPred10Version-cyberrealistic4-perpendicular.safetensors") ```