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.
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.
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.
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."
π΄ 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.
π΅ 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.
π΄ 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.
π΄ 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.
π Recommended Strength Settings for FF100+ π
π¨ Visuals: Boost up to 2.2 for vibrant and striking detail.
π Fusing Loras: Maintain 0.3 - 1.0 for seamless and safe integration with up to 6 FF Lora from FF100 above.
π Main Base Model for Testing:
π Introducing our upcoming batch of LoRAs numbered FF.100 to FF.176!
π Optimized new Size: ~200 - 400MB (depending on original models training and weights)
π·οΈ 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: π Sync CivitAI Repo: Up to date to 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
----------------------------
The following models served as the foundation for our extractions:
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 π - 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.
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
.
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.
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.
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.
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()
To revert the effects of fuse_lora()
:
pipe.unfuse_lora()
To control the influence of the LoRA parameters on the outputs:
pipe.fuse_lora(lora_scale=0.5)
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
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
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
Based on the extraction process, we observed the following differences in the text encoder across various models:
bluePencilXL_v021 β Text encoder available. Difference by 0.00140380859375
sdvn7Realartxl_beta2 β Text encoder available. Difference by 0.00362396240234375
4Guofeng4XL_v1125D π« Text encoder unavailable. Same as SDXL 1.0 Base
ambienceSDXL_a1 β Text encoder available. Difference by 0.003082275390625
angraSDXL10_v22 β Text encoder available. Difference by 0.001953125
animagineXL_v10 π« Text encoder unavailable. Same as SDXL 1.0 Base
animeArtDiffusionXL_alpha3 π« Text encoder unavailable. Same as SDXL 1.0 Base
astreapixieXLAnime_v16 β Text encoder available. Difference by 0.0029296875
bluePencilXL_v010 β Text encoder available. Difference by 0.00177001953125
breakdomainxl_v03d β Text encoder available. Difference by 0.0013427734375
canvasxl_Bfloat16V002 β Text encoder available. Difference by 0.00390625
cherryPickerXL_v20 β Text encoder available. Difference by 0.0016450881958007812
copaxTimelessxlSDXL1_v44 π« Text encoder unavailable. Same as SDXL 1.0 Base
counterfeitxl_v10 β Text encoder available. Difference by 0.001708984375
crystalClearXL_ccxl β Text encoder available. Difference by 0.0012865066528320312
deepblueXL_v006 β Text encoder available. Difference by 0.00200653076171875
dreamshaperXL10_alpha2Xl10 π« Text encoder unavailable. Same as SDXL 1.0 Base
duchaitenAiartSDXL_v10 π« Text encoder unavailable. Same as SDXL 1.0 Base
dynavisionXLAllInOneStylized_beta0371Bakedvae β Text encoder available. Difference by 0.00321197509765625
dynavisionXLAllInOneStylized_beta0411Bakedvae β Text encoder available. Difference by 0.0037841796875
envyoverdrivexl_v11 π« Text encoder unavailable. Same as SDXL 1.0 Base
envypoodaxl01_v10 β Text encoder available. Difference by 0.0011358261108398438
fantasticCharacters_v55 β Text encoder available. Difference by 0.00390625
fenrisxl_V55 β Text encoder available. Difference by 0.0086822509765625
fudukiMix_v10 β Text encoder available. Difference by 0.0011138916015625
infinianimexl_v16 β Text encoder available. Difference by 0.0048828125
juggernautXL_version1 β Text encoder available. Difference by 0.001953125
LahMysteriousSDXL_v330 π« Text encoder unavailable. Same as SDXL 1.0 Base
mbbxlUltimate_v10RC π« Text encoder unavailable. Same as SDXL 1.0 Base
miamodelSFWNSFWSDXL_v30 β Text encoder available. Difference by 0.0047607421875
morphxl_v10 β Text encoder available. Difference by 0.001861572265625
nightvisionXLPhotorealisticPortrait_beta0681Bakedvae β Text encoder available. Difference by 0.013885498046875
osorubeshiAlphaXL_z β Text encoder available. Difference by 0.005615234375
physiogenXL_v04 β Text encoder available. Difference by 0.00390625
protovisionXLHighFidelity3D_beta0520Bakedvae β Text encoder available. Difference by 0.007568359375
realitycheckXL_alpha11 β Text encoder available. Difference by 0.0015010833740234375
realmixXL_v10 β Text encoder available. Difference by 0.0023899078369140625
reproductionSDXL_v31 β Text encoder available. Difference by 0.00146484375
rundiffusionXL_beta β Text encoder available. Difference by 0.00196075439453125
samaritan3dCartoon_v40SDXL β Text encoder available. Difference by 0.0009765625
sdvn6Realxl_detailface π« Text encoder unavailable. Same as SDXL 1.0 Base
sdxl10ArienmixxlAsian_v10 β Text encoder available. Difference by 0.00048828125
sdxlbaseNsfwFaces_sdxlNsfwFaces03 β Text encoder available. Difference by 0.008056640625
sdxlFaetastic_v10 β Text encoder available. Difference by 0.0029296875
sdxlFixedvaeFp16Remove_baseFxiedVaeV2Fp16 π« Text encoder unavailable. Same as SDXL 1.0 Base
sdxlNijiV4_sdxlNijiV4 β Text encoder available. Difference by 0.0009765625
SDXLRonghua_v11 β Text encoder available. Difference by 0.0009765625
sdxlUnstableDiffusers_v5UnchainedSlayer β Text encoder available. Difference by 0.001251220703125
sdxlYamersAnimeUltra_yamersAnimeV2 β Text encoder available. Difference by 0.000732421875
sdXL_v10VAEFix π« Text encoder unavailable. Same as SDXL 1.0 Base
shikianimexl_v10 β Text encoder available. Difference by 0.0009765625
spectrumblendx_v10 β Text encoder available. Difference by 0.0013065338134765625
stableDiffusionXL_v30 π« Text encoder unavailable. Same as SDXL 1.0 Base
talmendoxlSDXL_v11Beta π« Text encoder unavailable. Same as SDXL 1.0 Base
wizard_v10 β Text encoder available. Difference by 0.000244140625
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.
Have you ever asked yourself, "How much space have I wasted on *.ckpt
and *.safetensors
checkpoints?" π€ Say hello to HowMuch: Checking checkpoint wasted space since... well, now!
π Enjoy this somewhat unnecessary, yet "fun-for-the-whole-family" DiskSpaceAnalyzer tool. π
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.
You can easily install HowMuch
via pip:
pip install howmuch
Clone the repository:
git clone https://github.com/1e-2/HowMuch.git
Navigate to the cloned directory and install:
cd HowMuch
pip install .
Run the tool without any arguments to scan all drives:
howmuch
Or, specify a particular directory or drive to scan:
howmuch --scan C:
Proudly maintained by Source Code Bulgaria Ltd & Black Swan Technologies.
π§ Email Us: [email protected] - For inquiries or support.
π Locations: Sofia | Istanbul | London
Connect with Us:
Our Websites:
π FFusion.ai
π FFAI.eu
π 1e-2.com