LoRA XL Models - CivitAI Repository 🌠

Welcome to the FFusion LoRA extracted models repository on Hugging Face & CivitAI! Here, we present a collection of models extracted using the Low-Rank Adaptation (LoRA) technique to provide a rich dataset for research and further exploration.

🌌 FFusion's Universe of 🧪 Curated LoRA Extractions

Our LoRAs are carefully extracted from a variety of models, allowing you to mix and match styles to create truly unique and artistic fusions. These extracted LoRAs are not a direct copy; they capture the essence of the original model, adding a creative influence "In the style of" or "Influenced by" the original work.

🧫 Research-Focused LoRAs

Please note that all FFusionAI extracted LoRAs are intended for research purposes only and are not licensed for commercial use. We encourage responsible and ethical utilization of these LoRAs to advance the field of AI-powered art creation.

⚠️ License & Usage Disclaimers

Please review the full license agreement before accessing or using the models.

The correct license and permissions can be found at:
https://huggingface.co/FFusion/
https://huggingface.co/FFusion/FFXL400/blob/main/LICENSE.md

"Model Weights: The weights used for the models/loras are provided "as is." FFusion AI and Source Code Bulgaria do not grant any rights for their commercial use. These weights are strictly for testing and experimental purposes. ORIGIN OF LORAS: The LORAs and weights provided are extracted from SDXL models (checkpoints).

All licenses, terms, and conditions set forth by the original checkpoint creator must be respected and adhered to.”

🔴 The models and weights available in this repository are strictly for research and testing purposes, with exceptions noted below. They are not generally intended for commercial use and are dependent on each individual LORA.

🔵 Exception for Commercial Use: The FFusionXL-BASE, FFusion-BaSE, di.FFUSION.ai-v2.1-768-BaSE-alpha, and di.ffusion.ai.Beta512 models are trained by FFusion AI using images for which we hold licenses. Users are advised to primarily use these models for a safer experience. These particular models are allowed for commercial use.

🔴 Disclaimer: FFusion AI, in conjunction with Source Code Bulgaria Ltd and BlackswanTechnologies, does not endorse or guarantee the content produced by the weights in each LORA. There’s potential for generating NSFW or offensive content. Collectively, we expressly disclaim responsibility for the outcomes and content produced by these weights.

🔴 Acknowledgement: The FFusionXL-BASE model model is a uniquely developed version by FFusion AI. Rights to this and associated modifications belong to FFusion AI and Source Code Bulgaria Ltd. Ensure adherence to both this license and any conditions set by Stability AI Ltd for referenced models.

Enhanced LoRA Flexibility

Dynamic Range: Unleash the full potential of your images with our flexible LoRA settings, offering a broad spectrum ranging from 0.2 for subtle nuances to 2.2 for intense transformations. This extended range surpasses standard limitations, providing unparalleled control to fine-tune visuals to your exact specifications.

Unparalleled Customization

Unlike conventional models that limit LoRA strength to a narrow range, FFusionAI provides unparalleled flexibility. Adjust LoRA strength from 0.2 for subtle effects to 2.2 for intense transformations. This extended range ensures that you have the tools to achieve the perfect stylistic blend, regardless of the base model or desired outcome.

🌟 Recommended Strength Settings for FF100+ 🌟

🎨 Visuals: Boost up to 2.2 for vibrant and striking detail.

🔗 Fusing Loras: Maintain 0.3 - 1.0 for seamless and safe integration with up to 6 FF Lora from FF100 above.

📚 Main Base Model for Testing:

📢 UPDATE: 10/22/23 📆

🌟 Introducing our upcoming batch of LoRAs numbered FF.100 to FF.176!

📈 Optimized new Size: ~200 - 400MB (depending on original models training and weights)
🏷️ New Naming: Optimized experience on Hugging Face for faster inference and testing.

pipe = DiffusionPipeline.from_pretrained(“FFusion/FFusionXL-BASE”, torch_dtype=torch.float16).to(“cuda”)
lora_model_id = “FFusion/400GB-LoraXL”
lora_filename = “FF.101.safetensors”
pipe.load_lora_weights(lora_model_id, weight_name=lora_filename)

CivitAI naming format stays the same.
Loading from CivitAI in diffusers

Todo: 🔄 Sync CivitAI Repo: Up to date to FF98

Latest FF60-FF98

Model: sdxlYamersRealism_version2 - Status: Text encoder is different. 0.0048828125 Model: animeChangefulXL_v10ReleasedCandidate - Status: Text encoder is different. 0.00390625 Model: brixlAMustInYour_v20Banu - Status: Text encoder is different. 0.001434326171875 Model: cinemaxAlphaSDXLCinema_alpha1 - Status: Text encoder is different. 0.00311279296875 Model: copaxTimelessxlSDXL1_v5 - Status: Text encoder is same. Model: dreamshaperXL10_alpha2Xl10 - Status: Text encoder is same. Model: endjourneyXL_v11 - Status: Text encoder is different. 0.0029296875 Model: explicitFreedomNSFW_beta - Status: Text encoder is different. 0.001220703125 Model: FinalAnimeCG_mk2a2 - Status: Text encoder is different. 0.00390625 Model: formulaxlXLComfyui_v20Pruned - Status: Text encoder is different. 0.002643585205078125 Model: furtasticxl_BetaEPOCHS3 - Status: Text encoder is different. 0.013824462890625 Model: galaxytimemachinesGTM_xlplusV10 - Status: Text encoder is different. 0.0012865066528320312 Model: hassakuSfwNsfwAlphav_alphaV02 - Status: Text encoder is different. 0.00390625 Model: juggernautXL_version4 - Status: Text encoder is different. 0.0019378662109375 Model: MOHAWK_v10BETA - Status: Text encoder is different. 0.00103759765625 Model: newone_v10 - Status: Text encoder is different. 0.001190185546875 Model: nightvisionXLPhotorealisticPortrait_v0743ReleaseBakedvae - Status: Text encoder is different. 0.009429931640625 Model: pyrosNSFWSDXL_v013e6 - Status: Text encoder is same. Model: pyrosSDModelsBlowjob_v0122022steps - Status: Text encoder is same. Model: realisticFreedomSFW_alpha - Status: Text encoder is different. 0.0011749267578125 Model: realisticStockPhoto_v10 - Status: Text encoder is different. 0.0011444091796875 Model: RealitiesEdgeXLANIME_20 - Status: Text encoder is different. 0.0018310546875 Model: RealitiesEdgeXL_30 - Status: Text encoder is different. 0.004150390625 Model: realvisxlV10_v10VAE - Status: Text encoder is different. 0.0029296875 Model: samaritan3dCartoon_v40SDXL - Status: Text encoder is different. 0.00390625 Model: sdvn6Realxl_detailface - Status: Text encoder is same. Model: sdxlNuclearGeneralPurposeSemi_v10 - Status: Text encoder is different. 0.003021240234375 Model: sdxlUnstableDiffusers_v6StabilityEater - Status: Text encoder is different. 0.0029296875 Model: sdxlYamersRealism_version2 - Status: Text encoder is different. 0.0048828125 Model: unsafexl_v20 - Status: Text encoder is different. 0.068359375 Model: venusxl_v11 - Status: Text encoder is different. 0.0013863444328308105 Model: xlYamersCartoonArcadia_v1 - Status: Text encoder is different. 0.0029296875 Model: FFusionXL-BASE-v1 - Status: Text encoder is different. 0.032245635986328125 Model: FFXL-400-v2 - Status: Text encoder is different. 0.023212432861328125 Model: FFXL400-LoRA-XL-FFusion-v1 - Status: Text encoder is different. 0.020404815673828125 Model: FFXXL-400-v2 - Status: Text encoder is different. 0.00948333740234375 Model: realcartoonXL_v2 - Status: Text encoder is different. 0.0015802383422851562 Model: sdxlYamersRealism_version2.FFai.lora64.safetensors UNet weight average magnitude: 4.154722048359913 UNet weight average strength: 0.010771295011342323 UNet Conv weight average magnitude: 4.015763928139778 UNet Conv weight average strength: 0.004715556773610134 Text Encoder (1) weight average magnitude: 3.958945306529754 Text Encoder (1) weight average strength: 0.013064685133728026 Text Encoder (2) weight average magnitude: 3.9970537933453656 Text Encoder (2) weight average strength: 0.01012922219208529 Model: FF.66.hassakuSfwNsfwAlphav_alphaV02.lora.safetensors UNet weight average magnitude: 4.6113617624162275 UNet weight average strength: 0.011981260592954776 UNet Conv weight average magnitude: 6.686307668617343 UNet Conv weight average strength: 0.006950538604713883 Text Encoder (1) weight average magnitude: 3.807746602732888 Text Encoder (1) weight average strength: 0.012745779610859834 Text Encoder (2) weight average magnitude: 3.729743715233202 Text Encoder (2) weight average strength: 0.009551327927254742 Model: FF.67.galaxytimemachinesGTM_xlplusV10.lora.safetensors UNet weight average magnitude: 5.2081857497500135 UNet weight average strength: 0.012861152998866098 UNet Conv weight average magnitude: 6.477215331015863 UNet Conv weight average strength: 0.005731545812523109 Text Encoder (1) weight average magnitude: 3.865321475649114 Text Encoder (1) weight average strength: 0.012968309181164591 Text Encoder (2) weight average magnitude: 3.791585137796209 Text Encoder (2) weight average strength: 0.009739622211064131 Model: FF.68.furtasticxl_BetaEPOCHS3.lora.safetensors UNet weight average magnitude: 4.82028448554389 UNet weight average strength: 0.012252009690673311 UNet Conv weight average magnitude: 6.774379998733585 UNet Conv weight average strength: 0.007177153983462227 Text Encoder (1) weight average magnitude: 4.20241893596518 Text Encoder (1) weight average strength: 0.01346020465857439 Text Encoder (2) weight average magnitude: 4.260738640446866 Text Encoder (2) weight average strength: 0.010471828656006711 Model: FF.69.formulaxlXLComfyui_v20Pruned.lora.safetensors UNet weight average magnitude: 4.194797467480407 UNet weight average strength: 0.010794051441520451 UNet Conv weight average magnitude: 5.658129971781666 UNet Conv weight average strength: 0.004699672960547711 Text Encoder (1) weight average magnitude: 3.9974802957054556 Text Encoder (1) weight average strength: 0.013097433444426298 Text Encoder (2) weight average magnitude: 4.090353610501367 Text Encoder (2) weight average strength: 0.010226978548569817 Model: FF.70.FinalAnimeCG_mk2a2.lora.safetensors UNet weight average magnitude: 5.832734982003316 UNet weight average strength: 0.013620979564593433 UNet Conv weight average magnitude: 6.588312134998715 UNet Conv weight average strength: 0.006310420276329548 Text Encoder (1) weight average magnitude: 3.856879807170544 Text Encoder (1) weight average strength: 0.012947154068967848 Text Encoder (2) weight average magnitude: 3.7769155501438316 Text Encoder (2) weight average strength: 0.009654614341923677 Model: FF.71.explicitFreedomNSFW_beta.lora.safetensors UNet weight average magnitude: 4.501298830893416 UNet weight average strength: 0.01109003259855744 UNet Conv weight average magnitude: 6.204555848757276 UNet Conv weight average strength: 0.005750268214362425 Text Encoder (1) weight average magnitude: 3.85944453350698 Text Encoder (1) weight average strength: 0.012919606802022875 Text Encoder (2) weight average magnitude: 3.9375385889629477 Text Encoder (2) weight average strength: 0.010088601556714144 Model: FF.72.endjourneyXL_v11.lora.safetensors UNet weight average magnitude: 4.202640614034873 UNet weight average strength: 0.010788684869548844 UNet Conv weight average magnitude: 5.80301284455635 UNet Conv weight average strength: 0.005029451652697187 Text Encoder (1) weight average magnitude: 3.835258093635928 Text Encoder (1) weight average strength: 0.012878727225694529 Text Encoder (2) weight average magnitude: 3.7550355683040344 Text Encoder (2) weight average strength: 0.009627099200498888 Model: FF.73.dreamshaperXL10_alpha2Xl10.lora.safetensors UNet weight average magnitude: 3.859263254032285 UNet weight average strength: 0.010177448403109668 UNet Conv weight average magnitude: 0.0 UNet Conv weight average strength: 0.0 Text Encoder: Not Found Model: FF.74.copaxTimelessxlSDXL1_v5.lora.safetensors UNet weight average magnitude: 4.006565464438231 UNet weight average strength: 0.010389718183037322 UNet Conv weight average magnitude: 5.738000089710234 UNet Conv weight average strength: 0.0048703539869873365 Text Encoder: Not Found Model: FF.75.cinemaxAlphaSDXLCinema_alpha1.lora.safetensors UNet weight average magnitude: 4.466204403397648 UNet weight average strength: 0.011222293042751443 UNet Conv weight average magnitude: 5.684097723570108 UNet Conv weight average strength: 0.004689726735887235 Text Encoder (1) weight average magnitude: 3.9233677697347935 Text Encoder (1) weight average strength: 0.013047985608868315 Text Encoder (2) weight average magnitude: 3.967672834668905 Text Encoder (2) weight average strength: 0.010161683571519127 Model: FF.76.brixlAMustInYour_v20Banu.lora.safetensors UNet weight average magnitude: 5.201652157233597 UNet weight average strength: 0.012340885235722432 UNet Conv weight average magnitude: 6.246570986909302 UNet Conv weight average strength: 0.005628776318139394 Text Encoder (1) weight average magnitude: 3.7901131354041215 Text Encoder (1) weight average strength: 0.012251635754363702 Text Encoder (2) weight average magnitude: 3.9011343266469787 Text Encoder (2) weight average strength: 0.009675557128661683 Model: FF.77.animeChangefulXL_v10ReleasedCandidate.lora.safetensors UNet weight average magnitude: 4.8712592588918255 UNet weight average strength: 0.011882757534620026 UNet Conv weight average magnitude: 6.307265147238472 UNet Conv weight average strength: 0.005707653219309981 Text Encoder (1) weight average magnitude: 3.806143895360976 Text Encoder (1) weight average strength: 0.012739821013629662 Text Encoder (2) weight average magnitude: 3.7378093050117975 Text Encoder (2) weight average strength: 0.009586058803350757 Model: FF.78.xlYamersCartoonArcadia_v1.lora.safetensors UNet weight average magnitude: 4.353353198959002 UNet weight average strength: 0.010753757289463425 UNet Conv weight average magnitude: 5.9177157902332835 UNet Conv weight average strength: 0.0051653985959496315 Text Encoder (1) weight average magnitude: 3.8127760281067853 Text Encoder (1) weight average strength: 0.012772330040804636 Text Encoder (2) weight average magnitude: 3.764581932297466 Text Encoder (2) weight average strength: 0.009682294095990565 Model: FF.79.venusxl_v11.lora.safetensors UNet weight average magnitude: 4.0781163529498725 UNet weight average strength: 0.01056802143213069 UNet Conv weight average magnitude: 5.725042873950945 UNet Conv weight average strength: 0.004766753768581111 Text Encoder (1) weight average magnitude: 3.8819661703272876 Text Encoder (1) weight average strength: 0.01297504551077796 Text Encoder (2) weight average magnitude: 3.8989897630581978 Text Encoder (2) weight average strength: 0.00999233670699671 Model: FF.80.unsafexl_v20.lora.safetensors UNet weight average magnitude: 4.433128703574937 UNet weight average strength: 0.01126235056722307 UNet Conv weight average magnitude: 5.6776551531768105 UNet Conv weight average strength: 0.004711627911345002 Text Encoder (1) weight average magnitude: 3.9928442365475028 Text Encoder (1) weight average strength: 0.013100078304973888 Text Encoder (2) weight average magnitude: 3.945462724939238 Text Encoder (2) weight average strength: 0.010062376848996262 Model: FF.81.sdxlYamersRealism_version2.lora.safetensors UNet weight average magnitude: 4.229406260655774 UNet weight average strength: 0.01076863108078825 UNet Conv weight average magnitude: 5.653783535189452 UNet Conv weight average strength: 0.004649401315378378 Text Encoder (1) weight average magnitude: 3.958945306529754 Text Encoder (1) weight average strength: 0.013064685133728026 Text Encoder (2) weight average magnitude: 3.9970537933453656 Text Encoder (2) weight average strength: 0.01012922219208529 Model: FF.82.sdxlUnstableDiffusers_v6StabilityEater.lora.safetensors UNet weight average magnitude: 4.387654105095919 UNet weight average strength: 0.010840575656477952 UNet Conv weight average magnitude: 5.859291158408854 UNet Conv weight average strength: 0.004964447160293478 Text Encoder (1) weight average magnitude: 3.8646596391683863 Text Encoder (1) weight average strength: 0.012911755181541458 Text Encoder (2) weight average magnitude: 3.840901404987889 Text Encoder (2) weight average strength: 0.009815472265736007 Model: FF.83.sdxlNuclearGeneralPurposeSemi_v10.lora.safetensors UNet weight average magnitude: 4.329690552630377 UNet weight average strength: 0.01081156604611163 UNet Conv weight average magnitude: 5.754435529197304 UNet Conv weight average strength: 0.004791491470688117 Text Encoder (1) weight average magnitude: 3.908995280978119 Text Encoder (1) weight average strength: 0.012984716052686607 Text Encoder (2) weight average magnitude: 3.8730233638208733 Text Encoder (2) weight average strength: 0.009816295838443996 Model: FF.84.sdvn6Realxl_detailface.lora.safetensors UNet weight average magnitude: 3.9204966894076203 UNet weight average strength: 0.010152018695796424 UNet Conv weight average magnitude: 5.609827023476847 UNet Conv weight average strength: 0.004578104347668462 Text Encoder: Not Found Model: FF.85.samaritan3dCartoon_v40SDXL.lora.safetensors UNet weight average magnitude: 4.1930053871423265 UNet weight average strength: 0.010823639858269587 UNet Conv weight average magnitude: 6.242507300692357 UNet Conv weight average strength: 0.006012499761466946 Text Encoder (1) weight average magnitude: 3.807746602732888 Text Encoder (1) weight average strength: 0.012745779610859834 Text Encoder (2) weight average magnitude: 3.729743715233202 Text Encoder (2) weight average strength: 0.009551327927254742 Model: FF.86.realvisxlV10_v10VAE.lora.safetensors UNet weight average magnitude: 4.035726046516959 UNet weight average strength: 0.01043685083171328 UNet Conv weight average magnitude: 5.780022388037139 UNet Conv weight average strength: 0.0049551385295671935 Text Encoder (1) weight average magnitude: 3.862534960968426 Text Encoder (1) weight average strength: 0.01291815120168007 Text Encoder (2) weight average magnitude: 3.8792245692334855 Text Encoder (2) weight average strength: 0.010027987691388776 Model: FF.87.RealitiesEdgeXLANIME_20.lora.safetensors UNet weight average magnitude: 4.322741449452443 UNet weight average strength: 0.011017050541178184 UNet Conv weight average magnitude: 5.957632120776351 UNet Conv weight average strength: 0.005321540223768453 Text Encoder (1) weight average magnitude: 3.9027693617053862 Text Encoder (1) weight average strength: 0.013066310297084008 Text Encoder (2) weight average magnitude: 3.941240896860996 Text Encoder (2) weight average strength: 0.010187814902599733 Model: FF.88.RealitiesEdgeXL_30.lora.safetensors UNet weight average magnitude: 4.527436449035657 UNet weight average strength: 0.011438576163998578 UNet Conv weight average magnitude: 6.042128532601058 UNet Conv weight average strength: 0.0053643976503331536 Text Encoder (1) weight average magnitude: 3.96435868300754 Text Encoder (1) weight average strength: 0.013183793628117942 Text Encoder (2) weight average magnitude: 4.03501811478197 Text Encoder (2) weight average strength: 0.01033219734045475 Model: FF.89.realisticStockPhoto_v10.lora.safetensors UNet weight average magnitude: 4.178010046544553 UNet weight average strength: 0.01060077238986419 UNet Conv weight average magnitude: 5.832883513120958 UNet Conv weight average strength: 0.005094057992644391 Text Encoder (1) weight average magnitude: 3.838598740372775 Text Encoder (1) weight average strength: 0.012775584451815206 Text Encoder (2) weight average magnitude: 3.8534473782218375 Text Encoder (2) weight average strength: 0.009703626948148766 Model: FF.90.realisticFreedomSFW_alpha.lora.safetensors UNet weight average magnitude: 4.570225351823505 UNet weight average strength: 0.011338880456799554 UNet Conv weight average magnitude: 6.107921122775599 UNet Conv weight average strength: 0.005313926393612039 Text Encoder (1) weight average magnitude: 3.9145800451769137 Text Encoder (1) weight average strength: 0.012987243885510853 Text Encoder (2) weight average magnitude: 3.9456476675702756 Text Encoder (2) weight average strength: 0.010086475486504298 Model: FF.91.realcartoonXL_v2.lora.safetensors UNet weight average magnitude: 4.264556294830096 UNet weight average strength: 0.010837268212782766 UNet Conv weight average magnitude: 5.775273580445967 UNet Conv weight average strength: 0.004823115907624419 Text Encoder (1) weight average magnitude: 3.868685000881062 Text Encoder (1) weight average strength: 0.012967535154814412 Text Encoder (2) weight average magnitude: 3.8942008722126786 Text Encoder (2) weight average strength: 0.009956078788817995 Model: FF.92.pyrosSDModelsBlowjob_v0122022steps.lora.safetensors UNet weight average magnitude: 4.29299465986103 UNet weight average strength: 0.011065152509191439 UNet Conv weight average magnitude: 6.148179389228268 UNet Conv weight average strength: 0.005785365500822891 Text Encoder: Not Found Model: FF.93.pyrosNSFWSDXL_v013e6.lora.safetensors UNet weight average magnitude: 4.462978487594761 UNet weight average strength: 0.011458003048327881 UNet Conv weight average magnitude: 6.365678967519903 UNet Conv weight average strength: 0.006252718402740558 Text Encoder: Not Found Model: FF.94.nightvisionXLPhotorealisticPortrait_v0743ReleaseBakedvae.lora.safetensors UNet weight average magnitude: 4.30821859959078 UNet weight average strength: 0.01092674471500856 UNet Conv weight average magnitude: 5.760595716272804 UNet Conv weight average strength: 0.0047913433799900915 Text Encoder (1) weight average magnitude: 4.082814836813033 Text Encoder (1) weight average strength: 0.013277437149876429 Text Encoder (2) weight average magnitude: 4.269554751742187 Text Encoder (2) weight average strength: 0.0104525629385582 Model: FF.95.newone_v10.lora.safetensors UNet weight average magnitude: 3.9863974933790827 UNet weight average strength: 0.010221166935769414 UNet Conv weight average magnitude: 5.591587011383119 UNet Conv weight average strength: 0.004544408523927106 Text Encoder (1) weight average magnitude: 3.826913276992613 Text Encoder (1) weight average strength: 0.012515731668562081 Text Encoder (2) weight average magnitude: 3.7789877235680827 Text Encoder (2) weight average strength: 0.008847150427050579 Model: FF.96.MOHAWK_v10BETA.lora.safetensors UNet weight average magnitude: 4.13427196290026 UNet weight average strength: 0.010604709463386349 UNet Conv weight average magnitude: 5.906059771550209 UNet Conv weight average strength: 0.005266774851315859 Text Encoder (1) weight average magnitude: 3.8816106810049615 Text Encoder (1) weight average strength: 0.013007851116722372 Text Encoder (2) weight average magnitude: 3.795246249757246 Text Encoder (2) weight average strength: 0.009741588405668723 Model: FF.97.juggernautXL_version4.lora.safetensors UNet weight average magnitude: 4.351658373013424 UNet weight average strength: 0.01097575598820061 UNet Conv weight average magnitude: 5.7254163997882515 UNet Conv weight average strength: 0.0048427100518286656 Text Encoder (1) weight average magnitude: 3.98009165065858 Text Encoder (1) weight average strength: 0.013189073899460014 Text Encoder (2) weight average magnitude: 4.452439746998783 Text Encoder (2) weight average strength: 0.010877184808674183

Model: FF.98.sdxlYamersRealism_version2.lora.safetensors UNet weight average magnitude: 4.229406260655774 UNet weight average strength: 0.01076863108078825 UNet Conv weight average magnitude: 5.653783535189452 UNet Conv weight average strength: 0.004649401315378378 Text Encoder (1) weight average magnitude: 3.958945306529754 Text Encoder (1) weight average strength: 0.013064685133728026 Text Encoder (2) weight average magnitude: 3.9970537933453656 Text Encoder (2) weight average strength: 0.01012922219208529 ––––––––––––––

📦 Base Models

The following models served as the foundation for our extractions:

🌟 Recommended Models for Inference

For those on the quest for ideal models to drive their inference tasks, we especially recommend:

FFusionXL-BASE - Our signature base model, meticulously trained with licensed images.
FFXL400 Combined LoRA Model 🚀 - A galactic blend of power and precision in the world of LoRA models.

Rest assured, our LoRAs, even at weight 1.0, maintain compatibility with most of the current SDXL models.

🔍 Extraction Details

Variants: Each base model was extracted into 4-5 distinct variants.
Extraction Depth: The models uploaded here contain approximately 70% of extracted data. These extractions yield a dataset size of around 400 GB.
Precision: We experimented with both float32 and float64 for optimal extraction results.
Differences Measurement: Singular Value Decomposition (SVD) was utilized to measure differences between the original and the tuned models. A threshold of 1e-3 was commonly used, although in some cases, 1e-5 and 1e-2 were tested.
Demonstration Parameters: For our demonstration, we employed “conv_dim”: 256 and “conv_alpha”: 256.

⚙️ Technical Notes

Most SDXL models in this collection are not traditionally “trained.” Instead, they are merged from previous SDXL 0.9 versions or created using other methods with the help of Comfy UI.
An important note for users: all models saved with Comfy add an extra key text_model.encoder.text_model.embeddings.position_ids. We’ve made necessary adjustments to ensure compatibility with the current scripts from Kohoya.

📈 Use Cases

These extracted models are intended for research and testing. They can be particularly useful for:

Investigating the potential of merging multiple LoRAs.
Weighting experiments with 1-5 LoRAs simultaneously.
Exploring the differences and similarities between LoRAs extracted from different base models.

FFusion LoRA Extracted Models - How to Use Guide 🧠

Welcome to the technical guide for using the FFusion LoRA extracted models. This document will walk you through the steps required to fuse LoRA parameters, load checkpoints, and perform inference.

Fusing LoRA Parameters 🔗

To merge the LoRA parameters with the original parameters of the underlying model(s), leading to a potential speedup in inference latency:

pipe.fuse_lora()

Unfusing LoRA Parameters ⛓️

To revert the effects of fuse_lora():

pipe.unfuse_lora()

Working with Different LoRA Scales 🎚️

To control the influence of the LoRA parameters on the outputs:

pipe.fuse_lora(lora_scale=0.5)

Working with FFusion Models 🔍

Here’s how to load and utilize our FFusion models:

from diffusers import DiffusionPipeline
import torch
pipeline_id = “FFusion/FFusionXL-BASE”
pipe = DiffusionPipeline.from_pretrained(pipeline_id, torch_dtype=torch.float16)
pipe.enable_model_cpu_offload()
lora_model_id = “FFusion/400GB-LoraXL”
lora_filename = “FFai.0038.Realitycheckxl_Alpha11.lora.safetensors”
pipe.load_lora_weights(lora_model_id, weight_name=lora_filename)
prompt = “papercut sonic”
image = pipe(prompt=prompt, num_inference_steps=20, generator=torch.manual_seed(0)).images[0]
image

Running Inference 🖼️

After loading the desired model, you can perform inference as follows:

generator = torch.manual_seed(0)
images_fusion = pipe(
“masterpiece, best quality, mountain”, output_type=“np”, generator=generator, num_inference_steps=25
).images

Library of Available LoRA Models 📚

You can choose any of the models from our repository on Hugging Face or the upcoming repository on CivitAI. Here’s a list of available models with lora_model_id = “FFusion/400GB-LoraXL”:

lora_filename =
- FFai.0001.4Guofeng4xl_V1125d.lora_Dim64.safetensors
- FFai.0002.4Guofeng4xl_V1125d.lora_Dim8.safetensors
- FFai.0003.4Guofeng4xl_V1125d.loraa.safetensors
- FFai.0004.Ambiencesdxl_A1.lora.safetensors
- FFai.0005.Ambiencesdxl_A1.lora_8.safetensors
- FFai.0006.Angrasdxl10_V22.lora.safetensors
- FFai.0007.Animaginexl_V10.lora.safetensors
- FFai.0008.Animeartdiffusionxl_Alpha3.lora.safetensors
- FFai.0009.Astreapixiexlanime_V16.lora.safetensors
- FFai.0010.Bluepencilxl_V010.lora.safetensors
- FFai.0011.Bluepencilxl_V021.lora.safetensors
- FFai.0012.Breakdomainxl_V03d.lora.safetensors
- FFai.0013.Canvasxl_Bfloat16v002.lora.safetensors
- FFai.0014.Cherrypickerxl_V20.lora.safetensors
- FFai.0015.Copaxtimelessxlsdxl1_V44.lora.safetensors
- FFai.0016.Counterfeitxl-Ffusionai-Alpha-Vae.lora.safetensors
- FFai.0017.Counterfeitxl_V10.lora.safetensors
- FFai.0018.Crystalclearxl_Ccxl.lora.safetensors
- FFai.0019.Deepbluexl_V006.lora.safetensors
- FFai.0020.Dream-Ffusion-Shaper.lora.safetensors
- FFai.0021.Dreamshaperxl10_Alpha2xl10.lora.safetensors
- FFai.0022.Duchaitenaiartsdxl_V10.lora.safetensors
- FFai.0023.Dynavisionxlallinonestylized_Beta0371bakedvae.lora.safetensors
- FFai.0024.Dynavisionxlallinonestylized_Beta0411bakedvae.lora.safetensors
- FFai.0025.Fantasticcharacters_V55.lora.safetensors
- FFai.0026.Fenrisxl_V55.lora.safetensors
- FFai.0027.Fudukimix_V10.lora.safetensors
- FFai.0028.Infinianimexl_V16.lora.safetensors
- FFai.0029.Juggernautxl_Version1.lora_1.safetensors
- FFai.0030.Lahmysterioussdxl_V330.lora.safetensors
- FFai.0031.Mbbxlultimate_V10rc.lora.safetensors
- FFai.0032.Miamodelsfwnsfwsdxl_V30.lora.safetensors
- FFai.0033.Morphxl_V10.lora.safetensors
- FFai.0034.Nightvisionxlphotorealisticportrait_Beta0681bakedvae.lora_1.safetensors
- FFai.0035.Osorubeshialphaxl_Z.lora.safetensors
- FFai.0036.Physiogenxl_V04.lora.safetensors
- FFai.0037.Protovisionxlhighfidelity3d_Beta0520bakedvae.lora.safetensors
- FFai.0038.Realitycheckxl_Alpha11.lora.safetensors
- FFai.0039.Realmixxl_V10.lora.safetensors
- FFai.0040.Reproductionsdxl_V31.lora.safetensors
- FFai.0041.Rundiffusionxl_Beta.lora.safetensors
- FFai.0042.Samaritan3dcartoon_V40sdxl.lora.safetensors
- FFai.0043.Sdvn6realxl_Detailface.lora.safetensors
- FFai.0044.Sdvn7realartxl_Beta2.lora.safetensors
- FFai.0045.Sdxl10arienmixxlasian_V10.lora.safetensors
- FFai.0046.Sdxlbasensfwfaces_Sdxlnsfwfaces03.lora.safetensors
- FFai.0047.Sdxlfaetastic_V10.lora.safetensors
- FFai.0048.Sdxlfixedvaefp16remove_Basefxiedvaev2fp16.lora.safetensors
- FFai.0049.Sdxlnijiv4_Sdxlnijiv4.lora.safetensors
- FFai.0050.Sdxlronghua_V11.lora.safetensors
- FFai.0051.Sdxlunstablediffusers_V5unchainedslayer.lora.safetensors
- FFai.0052.Sdxlyamersanimeultra_Yamersanimev2.lora.safetensors
- FFai.0053.Shikianimexl_V10.lora.safetensors
- FFai.0054.Spectrumblendx_V10.lora.safetensors
- FFai.0055.Stablediffusionxl_V30.lora.safetensors
- FFai.0056.Talmendoxlsdxl_V11beta.lora.safetensors
- FFai.0057.Wizard_V10.lora.safetensors
- FFai.0058.Wyvernmix15xl_Xlv11.lora.safetensors
- FFai.0059.Xl13asmodeussfwnsfw_V17bakedvae.lora.safetensors
- FFai.0060.Xl3experimentalsd10xl_V10.lora.safetensors
- FFai.0061.Xl6hephaistossd10xlsfw_V21bakedvaefp16fix.lora.safetensors
- FFai.0062.Xlperfectdesign_V2ultimateartwork.lora.safetensors
- FFai.0063.Xlyamersrealistic_V3.lora.safetensors
- FFai.0064.Xxmix9realisticsdxl_Testv20.lora.safetensors
- FFai.0065.Zavychromaxl_B2.lora.safetensors

📊 Text Encoder Difference Overview

Based on the extraction process, we observed the following differences in the text encoder across various models:

bluePencilXL_v021 ✅ Text encoder available. Difference by 0.00140380859375
sdvn7Realartxl_beta2 ✅ Text encoder available. Difference by 0.00362396240234375
4Guofeng4XL_v1125D 🚫 Text encoder unavailable. Same as SDXL 1.0 Base
ambienceSDXL_a1 ✅ Text encoder available. Difference by 0.003082275390625
angraSDXL10_v22 ✅ Text encoder available. Difference by 0.001953125
animagineXL_v10 🚫 Text encoder unavailable. Same as SDXL 1.0 Base
animeArtDiffusionXL_alpha3 🚫 Text encoder unavailable. Same as SDXL 1.0 Base
astreapixieXLAnime_v16 ✅ Text encoder available. Difference by 0.0029296875
bluePencilXL_v010 ✅ Text encoder available. Difference by 0.00177001953125
breakdomainxl_v03d ✅ Text encoder available. Difference by 0.0013427734375
canvasxl_Bfloat16V002 ✅ Text encoder available. Difference by 0.00390625
cherryPickerXL_v20 ✅ Text encoder available. Difference by 0.0016450881958007812
copaxTimelessxlSDXL1_v44 🚫 Text encoder unavailable. Same as SDXL 1.0 Base
counterfeitxl_v10 ✅ Text encoder available. Difference by 0.001708984375
crystalClearXL_ccxl ✅ Text encoder available. Difference by 0.0012865066528320312
deepblueXL_v006 ✅ Text encoder available. Difference by 0.00200653076171875
dreamshaperXL10_alpha2Xl10 🚫 Text encoder unavailable. Same as SDXL 1.0 Base
duchaitenAiartSDXL_v10 🚫 Text encoder unavailable. Same as SDXL 1.0 Base
dynavisionXLAllInOneStylized_beta0371Bakedvae ✅ Text encoder available. Difference by 0.00321197509765625
dynavisionXLAllInOneStylized_beta0411Bakedvae ✅ Text encoder available. Difference by 0.0037841796875
envyoverdrivexl_v11 🚫 Text encoder unavailable. Same as SDXL 1.0 Base
envypoodaxl01_v10 ✅ Text encoder available. Difference by 0.0011358261108398438
fantasticCharacters_v55 ✅ Text encoder available. Difference by 0.00390625
fenrisxl_V55 ✅ Text encoder available. Difference by 0.0086822509765625
fudukiMix_v10 ✅ Text encoder available. Difference by 0.0011138916015625
infinianimexl_v16 ✅ Text encoder available. Difference by 0.0048828125
juggernautXL_version1 ✅ Text encoder available. Difference by 0.001953125
LahMysteriousSDXL_v330 🚫 Text encoder unavailable. Same as SDXL 1.0 Base
mbbxlUltimate_v10RC 🚫 Text encoder unavailable. Same as SDXL 1.0 Base
miamodelSFWNSFWSDXL_v30 ✅ Text encoder available. Difference by 0.0047607421875
morphxl_v10 ✅ Text encoder available. Difference by 0.001861572265625
nightvisionXLPhotorealisticPortrait_beta0681Bakedvae ✅ Text encoder available. Difference by 0.013885498046875
osorubeshiAlphaXL_z ✅ Text encoder available. Difference by 0.005615234375
physiogenXL_v04 ✅ Text encoder available. Difference by 0.00390625
protovisionXLHighFidelity3D_beta0520Bakedvae ✅ Text encoder available. Difference by 0.007568359375
realitycheckXL_alpha11 ✅ Text encoder available. Difference by 0.0015010833740234375
realmixXL_v10 ✅ Text encoder available. Difference by 0.0023899078369140625
reproductionSDXL_v31 ✅ Text encoder available. Difference by 0.00146484375
rundiffusionXL_beta ✅ Text encoder available. Difference by 0.00196075439453125
samaritan3dCartoon_v40SDXL ✅ Text encoder available. Difference by 0.0009765625
sdvn6Realxl_detailface 🚫 Text encoder unavailable. Same as SDXL 1.0 Base
sdxl10ArienmixxlAsian_v10 ✅ Text encoder available. Difference by 0.00048828125
sdxlbaseNsfwFaces_sdxlNsfwFaces03 ✅ Text encoder available. Difference by 0.008056640625
sdxlFaetastic_v10 ✅ Text encoder available. Difference by 0.0029296875
sdxlFixedvaeFp16Remove_baseFxiedVaeV2Fp16 🚫 Text encoder unavailable. Same as SDXL 1.0 Base
sdxlNijiV4_sdxlNijiV4 ✅ Text encoder available. Difference by 0.0009765625
SDXLRonghua_v11 ✅ Text encoder available. Difference by 0.0009765625
sdxlUnstableDiffusers_v5UnchainedSlayer ✅ Text encoder available. Difference by 0.001251220703125
sdxlYamersAnimeUltra_yamersAnimeV2 ✅ Text encoder available. Difference by 0.000732421875
sdXL_v10VAEFix 🚫 Text encoder unavailable. Same as SDXL 1.0 Base
shikianimexl_v10 ✅ Text encoder available. Difference by 0.0009765625
spectrumblendx_v10 ✅ Text encoder available. Difference by 0.0013065338134765625
stableDiffusionXL_v30 🚫 Text encoder unavailable. Same as SDXL 1.0 Base
talmendoxlSDXL_v11Beta 🚫 Text encoder unavailable. Same as SDXL 1.0 Base
wizard_v10 ✅ Text encoder available. Difference by 0.000244140625

🎉 Acknowledgements & Citations

A huge shoutout to the community for their continued support and feedback. Together, we are pushing the boundaries of what’s possible with machine learning!

We would also like to acknowledge and give credit to the following projects and authors:

ComfyUI: We’ve used and modified portions of ComfyUI for our work.
kohya-ss/sd-scripts and bmaltais: Our work also incorporates modifications from kohya-ss/sd-scripts.
lora-inspector: We’ve benefited from the lora-inspector project.
KohakuBlueleaf: Special mention to KohakuBlueleaf for their invaluable contributions.

HowMuch ???

Have you ever asked yourself, “How much space have I wasted on .ckpt and .safetensors checkpoints?” 🤔 Say hello to HowMuch: Checking checkpoint wasted space since… well, now!

😄 Enjoy this somewhat unnecessary, yet “fun-for-the-whole-family” DiskSpaceAnalyzer tool. 😄

Overview

HowMuch is a Python tool designed to scan your drives (or a specified directory) and report on the total space used by files with specific extensions, mainly .ckpt and .safetensors.

It outputs:

The total storage capacity of each scanned drive or directory.
The space occupied by .ckpt and .safetensors files.
The free space available.
A neat bar chart visualizing the above data.

Installation

GitHub

From PyPI

You can easily install HowMuch via pip:

pip install howmuch

From Source

Clone the repository:

git clone https://github.com/1e-2/HowMuch.git

Navigate to the cloned directory and install:
```
cd HowMuch
pip install .
```

Usage

Run the tool without any arguments to scan all drives:

howmuch

Or, specify a particular directory or drive to scan:

howmuch –scan C:

🌐 FFusion.ai Contact Information

Proudly maintained by Source Code Bulgaria Ltd & Black Swan Technologies.

📧 Email Us: [email protected] - For inquiries or support.
🌍 Locations: Sofia | Istanbul | London

Connect with Us:

🐙 GitHub
😊 Hugging Face
💡 Civitai

Our Websites:

🌐 FFusion.ai
🌌 FFAI.eu
🔗 1e-2.com

모델 유형	LORA
기본 모델	SDXL 1.0
게시일	2023-11-07

400GB-LoRA-XL-Repository

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