You can get Gwen3, KreaLife1, KreaEdit1, Klein4, Cat1 or Hyper1 for $10 and Ultra5, Zuna1 or Zia1 for $5.50 on Ko-Fi. 30-day membership subscriptions available there too. Any problem? Need another payment option? Contact me via chat.
To create up to 85 free images per day in highest quality you can use Big Love here. For discussing photorealistic image generation join me on Discord.
Big Love Gwen is a finetune of Qwen Edit 2511 and can do NSFW image editing. It produces more realistic and sharp images with better skin texture & genitals than other Qwen checkpoints/loras. Txt2img is lower quality, but generates nice results too.
It is recommended to use ComfyUI. The Gwen workflows offer a skin enhance feature that is not available in Forge Neo. Move the Gwen model file into the diffusion_model sub folder of the models folder of ComfyUI, qwen_2.5_vl_7b_fp8_scaled.safetensors into the text_encoder sub folder and qwen_image_vae.safetensors into the vae sub folder.
For training a lora read here.
Settings are 6-8 steps (3 steps for upscaling), cfg 1-1.5, Euler sampler, Beta scheduler, 832x1216 or 1024x1536 pixels. Drag'n'drop showcase images into ComfyUI for a workflow.
KreaEdit/KreaLife Big Love are a finetune of Krea 2 that can do txt2img and NSFW image editing. It is more photorealistic, a lot more NSFW-capable and has better skin texture than the original Krea 2. They produce only photorealistic images with booru tags (not anime like other Krea 2 models). They offers the best anatomy (with the least problems) of all Big Love checkpoints. KreaEdit produces more professional style images while KreaLife is trained more on amateur & candid images.
Move the model file into the diffusion_model sub folder of the models folder of ComfyUI, qwen3vl_4b_bf16.safetensors (12+ GB VRAM) or qwen3vl_4b_fp8_scaled.safetensors (6-8 GB VRAM) into the text_encoder sub folder and qwen_image_vae.safetensors into the vae sub folder. To make the GGUF version work in ComfyUI, you need to unzip the second .zip file from Optional Files into the custom_nodes sub folder.
For editing they require the Krea2Edit nodes that can be installed via Comfy Manager by searching for "Krea 2 Identity Edit". For more face consistency try increasing the grounding_px parameter to 1024 and ref_boost to 3 or 4.
Settings are 8 steps (3-4 steps for upscaling), cfg1, er_sde sampler, Beta scheduler, 1024x1536 pixels. Drag'n'drop showcase images into ComfyUI for a workflow.
Big Love Klein is a fine-tune of Flux 2 klein. It can do txt2img and also edit images with prompts. It only needs 4 steps, so is quite fast. Check the "About this version" box on the right for info on the individual variants. Some are up to 3x faster.
It is recommended to use it with ComfyUI. Put the downloaded model into the diffusion models sub folder of ComfyUI. You also need qwen_3_8b_fp8mixed.safetensors in the text_encoders sub folder (Qwen3-8B-Q5_K_M.gguf wth 8 GB VRAM) and flux2-vae.safetensors in the vae sub folder. Check out these anatomy tips.
Settings are 4 steps (2 steps for upscaling), cfg1, Euler sampler, Beta or Simple scheduler, 832x1216, 1024x1536, 1280x1920 or 1536x2240 pixels. Drag'n'drop showcase images into ComfyUI for a workflow.
Big Love Cat is a finetune of LongCat and allows NSFW image editing. It reproduces faces extremely well, with almost every image, so a lot more reliable than Klein & Gwen. It is only 6B and needs 8 steps cfg 1. Same Apache 2.0 license and text encoder as Qwen Image but 8 GB VRAM are enough. Txt2img and sex scenes are still experimental. The base model was only trained on one input image & only picks up random details from a 2nd image. The bf16 version of Cat is faster than Klein & Gwen. The mxfp8 version is 1.6x faster than bf16 and just as fast as Gwen.
There is a new detailer workflow below that I developed for Cat but can be used with any model's images. It uses Photo, Ultra, Hyper or Klein for detailing nipples and pussies.
It is recommended to use ComfyUI. Move the model file into the diffusion_model sub folder of the models folder of ComfyUI, qwen_2.5_vl_7b_fp8_scaled.safetensors into the text_encoder sub folder and ae.safetensors into the VAE sub folder.
Training speed is more than 2x faster than any transformer model that I know. For training a lora you need SimpleTuner, which requires WSL under Windows and has a WebUI similar to AI-Toolkit. Detailed instructions will become available soon...
Big Love Cat produces the sharpest images with er_sde/Normal. In a few cases this adds subtle color grain which can be avoided by increasing steps to 12. er_sde/beta and Euler produce softer images without grain.
Settings are 8-12 steps (4 steps for upscaling), cfg 1, er_sde/Normal sampler/scheduler (Softer: Euler/Beta or er_sde/Beta), 832x1216, 1024x1536 or 1232x1824 pixels. Drag'n'drop showcase images into ComfyUI for a workflow.
Big Love Eryn is a fine-tune of Ernie-Image(-Turbo). You can run it locally with ComfyUI and Forge Neo. The fp8 version works with 8 & 12 GB VRAM. Use the (pruned) bf16 version if you have 16 GB VRAM or more. The "Full" versions are only meant for training a lora (coming soon!). Put the downloaded model into the diffusion models sub folder of ComfyUI or the StableDiffusion sub folder of Forge Neo. You additionally need to place ministral-3-3b.safetensors in the text_encoder sub folder and flux2-vae.safetensors in the VAE sub folder.
Settings are 4-6 steps (3-4 steps for upscaling), cfg1, Euler sampler, Beta scheduler, 832x1216 or 1024x1536 pixels. Drag'n'drop showcase images into ComfyUI for a workflow.
Big Love Hyper supports generating at image sizes of 1664x2432 (4 megapixel) and higher with SDXL. Can be easily upscaled to 9 megapixel unlike the normal low-res images. Hyper currently has not fully stable anatomy, so needs more runs. Some prompts work better than others. It produces highly detailed and life-like images close to real photos. It has a special quality that cannot be achieved by just upscaling. The Hyper versions of Big Love are pay-only and special license conditions apply (see below).
Settings are DMD2 lora with strength 1.0, LCM Exponential, 8 steps, cfg 1, clip skip 2, 1664x2432 or 1536x2240. Upscale with img2img with DMD2 lora with strength 1.0, same prompt, LCM Exponential, 1.25-1.5x, 4-8 steps, cfg 1, 0.3-0.5 denoise, clip skip 2. Look below for a ComfyUI workflow.
Big Love ZT, Zia or Zuna are fine-tunes of Z-Image(-Turbo) on the Big Love dataset. You can run it locally with ComfyUI and Forge Neo. The fp8 version works faster with 8 GB VRAM but produces more noise so may sometimes look more realistic, but details are not as good. Use the (pruned) bf16 version if you have 12 GB VRAM or more. The "Full" version is only meant for training a lora. Put the downloaded model into the diffusion models sub folder of ComfyUI or the StableDiffusion sub folder of Forge Neo. To make Big Love ZT/Zia/Zuna work you additionally need to place qwen3_4b.safetensors in the text_encoder sub folder and ae.saftendors in the VAE sub folder.
Settings are 8 steps, cfg1, Euler or DPM++ 2s a RF sampler, Normal or Simple or Beta scheduler, 832x1216, 1024x1536 or 1280x1920 pixels. For upscaling 8 steps, cfg1, Euler sampler, Normal or Simple or Beta scheduler, 1.5x upscale. Here is a ComfyUI workflow embedded in a image.
Big Love Ultra supports generating at image sizes of 1280x1870, 1360x1984 and higher. Can be easily upscaled to 6 megapixel unlike the normal low-res images. More photorealistic and detailed. A special quality that cannot be achieved by just upscaling. Ultra produces more details & sharpness when upscaling and detailing low-res images. The Ultra versions of Big Love are pay-only and special license conditions apply. See below.
Settings are DMD2 lora with strength 1.0, LCM Exponential, 8 steps, cfg 1, clip skip 2, 1280x1864 or 1360x1984. Upscale with img2img with DMD2 lora with strength 1.0, same prompt, LCM Exponential, 1.25-1.5x, 4-8 steps, cfg 1, lora strength 1.0, 0.3-0.5 denoise, clip skip 2. Look below for a ComfyUI workflow.
Big Love Photo and Insta1 are finetuned versions of XL. Lust1 is a finetuned version of Lustify merged with Photo. They were trained on thousands of images and dozens of new concepts. Why they are the most realistic and versatile. For more details and prompting Photo1 read this article.
Settings are DMD2 lora with strength 1.0, LCM Exponential, 8 steps, cfg 1, clip skip 2, 832x1216 or 1024x1496. Upscale with img2img with DMD2 lora, same prompt, LCM Exponential, 1.25-1.5, 4-8 steps, cfg 1, lora strength 1.0, 0.3-0.5 denoise, clip skip 2. Look below for a ComfyUI workflow.
Big Love XL is a combination of 5 different training branches of SDXL: original SDXL, bigASP, NatVis, Anteros and Pony. With a bit of Pony in it, some Pony loras (poses, characters) work too. It outputs a more photorealistic & creative look than the Pony versions and can also do paintings & cartoon.
Settings are DMD2 lora with strength 1.0, LCM Exponential, 8 steps, cfg 1-1.5, clip skip 2, 832x1216 or 1024x1496. Upscale with img2img with DMD2 lora, same prompt, LCM Exponential, 1.5-2x, 8-12 steps (XL1/XL2), 4-8 steps (XL2.5-XL4), cfg 1, lora strength 1.0, 0.3-0.5 denoise, clip skip 2. Look below for a ComfyUI workflow.
Big Love Pony produces different images than both Pony & SDXL-based models. Pony tags are understood, but interpreted a bit differently. Some images lean more in the one or other direction depending on the prompt. It works with Pony loras as well as normal SDXL ones. It can turn anime/cartoon into photorealistic images in img2img. Pony3 includes a bit of Illustrious.
Settings are DMD2 lora with strength 1.0, LCM Exponential, 8 steps, cfg 1-1.5, clip skip 2, 832x1216 or 1024x1496. Upscale with img2img with DMD2 lora, same prompt, LCM Exponential, 1.5-2x, 8-12 steps, cfg 1, lora strength 1.0, 0.3-0.5 denoise, clip skip 2.
Generation Workflows
Download one of the following images and drag'n'drop it onto ComfyUI:
Z-Turbo/Z-Base txt2img & Upscale Workflow (recommended)
SDLX DMD2 txt2img & Upscale Workflow (recommended)
SDXL DMD2 txt2ing & Upscale for Big Love Ultra
SDXL DMD2 img2img Workflow
SDXL Lightning Workflow
Workflows for all other models are embedded in the showcase images above.
Detailer Workflows
Here are the detailer workflows that I use myself. Drag'n'drop the images linked below into Comfy:
Photo/Ultra/Hyper Detailer Workflow
Klein Detailer Workflow
Check the note at the top of the workflow for downloading the necessary detection models and where to place them.
Krea 2 Trained Concepts
KreaLife1: amateur photo, outdoor sex, party, real life, candid, candid shot, outdoor flashing, public indecency, public nudity, beach life, 3d selfie
film grain, low image quality, low contrast, flash light, blurry, soft skin, overexposure
69 position, anal gape, cumshot, dildo insertion, double oral, handjob, innie pussy, object insertion, anal fingering, cuddling, cum swapping, female masturbation, finger licking, footjob, french kiss, funny tongue out, orgasm face, penis licking, pussy licking, vaginal fingering, partner fingering
SDLX Trained Concepts
Newer versions of Big Love include the concepts of older versions, e.g. Photo4 can do everything that Photo1 to Photo3 can do and more. The only exception are the Insta concepts, but they have been partially added to never versions too.
Photo6/Ultra5: ai-style, bodyscape, butt plug, candid amateur, cumshot, illustrious-style, outdoor sex, partner fingering, photoart, innie pussy, ray-style, rebellious, reflection, sensual, sexy ass, sweetheart, wedgie
Photo5/Ultra4/Hyper1: alluring, anal sex, artistic photo, artistic pinup, charming, cum portrait, cute asian, cute pinup, cute portrait, double oral, dreamy-style, face pov, fantasy pinup, fantasy-style, kai-style, lowkey, mj-style, outdoor flashing, photo art, pole dance, public indecency, public nudity, rock climbing, scify-style, sword pose, vaginal sex
Photo4/Photo4.5/Ultra2/Ultra3: 2girls kissing, acrobatic sex, average face, beautiful face, amateur pinup, anal fingering, artistic portrait, cuddling, cum swapping, doggystyle pov, even skin color, fashion photo, female masturbation, female pov, finger licking, food porn, footjob, french kiss, full nelson, funny movie, funny tongue out, insta cute, legs pov, low contrast, mirror portrait, nude pose, oral pov, orgasm face, outdoor nude, penis licking, pinup photo, pro photo, pro portrait, pussy licking, sex pov, sexy portrait, vaginal fingering, waterfall
Photo3/Lust1/Ultra1: 360 degree photo, 3d selfie, 69 position, adorable, alt beauty, anal gape, anal sex, average face, beach life, beautiful, beautiful face, candidness, cum, cute, deepthroat, dildo insertion, double exposure, enthusiastic, extreme pose, faces, fashion photo, female pov, fisting, follow me pov, girl next door, gorgeous, handjob, heroin chic, huge feet, huge hands, huge nipples, light rays, light streaks, lighting, low/mid/high contrast, lowkey/midkey/highkey, low/mid/high saturation, middle finger, motion blur, object insertion, detailed eyes, teeth, pro photo, pussy gape, real life, rooftop, round ass, sad, sexy pose, skin texture, skin tone, spread pussy, squirting, street portrait, testicle licking, testicle sucking, vaginal sex, voluminous hair, water splash
Insta1: amateur photo, fashion photo, insta selfie, pinup photo, pro photo, real life, big ass, bimbo, cute, luxurious, adorable, enthusiastic, average face, beautiful face, detailed eyes, sexy legs.
Photo2: 3d selfie, 69 position, adorable, alt beauty , amateur photo, ball licking, ball sucking, beach life, bubble butt, low/mid/high contrast, dildo insertion, double exposure, enthusiastic, extreme pose, female pov, follow me pov, forced perspective, girl next door, gorgeous, handjob, heroin chic, huge feet, huge hands, huge nipples, light rays, light streaks, lighting, middle finger, motion blur, no tan lines, object insertion, pussy gape, rooftop, sad, low/mid/high saturation, sexy pose, squirting, street portrait, water splash.
Photo1: amateur photo, pro photo, lighting, lowkey, midkey, highkey, beautiful, cute, candid, real life, average face, remarkable face, voluminous hair, skin tone, skin texture, 360 degree photo, spread pussy, deepthroat, fisting, anal gape, anal sex, vaginal sex.
Training a (character) lora
My advice is this: Take 10-30 high quality images (at least 50-100 for styles or poses), download OneTrainer, click the SDXL lora preset, choose Big Love as the base checkpoint, add your images as a concept, add tags on the Tools tab, and start training. If you train on Big Love Ultra change the training resolution to 1536 and provide 1248x1832 images.
You will only get the full Big Love quality by training on real photos or extremely photorealistic images, which is usually not the case with a fictional character. It is all about image quality and not choosing boring images. Don't add posing images to a character lora, because Big Love provides the posing later for it. Focus mainly on good portraits with a few upper and full body images. Rather fewer higher quality images than a lot of average images. Read here for traing a lora on Big Love ZT2, ZT3, Zia1, Zuna1 or Eryn1.
Fixing Anatomy
If you want to keep the seed and repair anatomical problems in an image, activate the Extra checkbox in A1111/Forge and set Variation Strength to 0.01 to 0.1. Then generate until anatomy is fine. In Comfy there are sampler nodes that support variation seed (e.g. Inspire Pack), which do the same thing. Also possible to change steps or add commas to the prompt, but I do not recommend it. Extra/Variation Seed is more powerful and convenient as it gives you endless variations with just one click. There is always a variation which looks similar or even better with great anatomy.
You don't need negative prompts for this. They are rather ineffective. You can also change the positive prompt to suppress things. Anatomy problems are also created by the prompt if you prompt contradicting poses that the model cannot combine. Better to fix the prompt first then.
Reducing Saturation, Warm Colors and Sharpness
These SDXL loras reduces the saturation and change the color temperature without reducing image quality. The lora strength defines the effect. Negative values increase saturation or add more warmth. To make an image softer use a lower strength for the DMD2 lora, e.g. 0.95, 0.9, 0.85.
Big Love Hyper/Ultra/Photo Sizes
Big Love Hyper supports these image sizes:
1664x2432 (recommend)
1536x2240
Big Love Ultra supports these image sizes:
1360x1984
1280x1872 (recommend)
Big Love Photo supports these image sizes:
1024x1496 (recommend)
832x1216
You can also use the 16:9 or 2:3 versions of these image sizes as well as landscape orientation, but the above should be more reliable.
The higher the image size, the lower the probability of good results. If you get too many problems with a higher image size, switch to the lower one. Some prompts do higher sizes fine, some do not. Do not use a lower image size than the recommended one, otherwise image quality will be lower. With higher image sizes anatomy problems occur too often.
Remove fill words and unusual tags in the prompt. They can cause a quality reduction with Big Love Ultra/Hyper as they were not trained. Shorter prompts should work better as it is less likely that bad or untrained tags are in it.
SFW Output - No Tits Please
"Is there a trick so that Big Love doesn't always generate raised shirts or visible breasts?" I get this asked so often, while it is so obvious. Big Love knows what men want so it gives it to them. Negatives don't work that well for it. So you got to speak to it in the positive prompt like you were taking to a nun. "Breasts? How dare you speak such an obscene word to me." Don't mention breasts or any of these sexy parts. Instead describe clothes a lot. Don't write down your impure thoughts. God forbid! Yeah, I know, so hard. Describe her body shape, which also implies certain tits underneath the clothes.
XL Prompting Advice
SDXL prompts & prompts from various SDXL checkpoints work with it. Pony prompts too, but they create a more photorealistic look. Natural language prompts tend to create artistic glamour images with less skin detail while normal tags do more photo-style images. Big Love XL gives individual words more attention, so you don't need to rework prompts like Big Love Pony requires sometimes.
XL1/XL2 has a tendancy towards cuteness and bright skin. If you get too much of it, remove words like cute, sweet, pale/fair skin & flash from the prompt. It also creates realistical analog photos with reduced image quality. Sometimes better to remove terms like analog or grain to increase quality. Decrease cfg to get a more natural look.
XL2.5 can sometimes get too sharp. Reduce cfg or use less steps in img2img to make images softer.
Pony Prompting Advice
Pony prompts & prompts from other checkpoints work with it. Score tags and fill words like masterpiece or perfect skin have as good as no effect usually. A negative prompt is often unnecessary unless you want to make something vanish or avoid underage, but it can also change the style of the image.
Pure booru tags and some other samplers may produce Pony style. Photographic terms or a simple prompts ensure a photo look. Sometimes it refuses to produce medium shots, portraits or close-ups unless you weigh the term heavily or remove feet, shoes, high heels, boots etc. from the prompt. wavy hair sometimes does not look so great.
If it refuses to do porn, try simplifying the prompt. If you want to do a portrait, don't describe surroundings too much. If you want to do porn, describe the action mainly and don't focus on the people or surroundings in the prompt. The largest part of the prompt should be about the main subject of the image.
If a prompt does not produce the intended image, you often only need to modify it a bit to make it work perfectly.
Using Character Loras
Big Love Pony supports Pony characters, but they look like real humans. There were some complaints about them not working, but the problem was not the model itself so far. So here are some tips:
* Try Pony as well as SDXL character loras
* Use a lora weight up to 1.5 if it does not reduce quality
* If it is a well known character, add the name in the prompt and also give it a higher weight if necessary.
* Check your negative prompt for problems. Delete it if necessary and rewrite it from scratch.
* Render a lot of images to be able to pick those with the best resemblance.
More SDXL Photorealism:
You can highly improve the images generated with this model by using img2img, upscaling, detailing etc. The SDXL Lightning lora enhances the look and constrast despite only 8 steps. Alternatively, the SDXL DMD2 lora produces a sharp, but more natural look with less contrast. Also check out the Subtle Style loras, which nicely enhance images.
Big Love License
Big Love SDXL versions are licensed under CreativeML Open RAIL++M (dated July 26, 2023), Big Love Z-Image, Ernie, Qwen & Longcat versions are licensed under Apache 2.0, Big Love Klein versions are licensed under the FLUX Non-Commercial License v2, and Krea 2 versions of Big Love are licensed under the KREA 2 Community License with the following additional terms:
For clarity, the following version tiers are defined:
Restricted versions: Ultra, Hyper, Klein, Zia, Zuna, Eryn, Gwen, Cat, KreaEdit, KreaLife
Open versions: Pony, XL, Photo, Insta, Lust, ZT
1. You may use Big Love without crediting the creator.
2. You may sell the images that it generates.
3. You may only run the official Big Love versions of the SubtleShader account on Civitai and Tensor Art. Running it on other public or shared servers commercially (including other Civitai and Tensor Art accounts) requires a separate license or permission from the creator.
4. You may not sell this model or merges of this model.
5. You may not merge, share merges of, or share LoRA extractions incorporating Restricted versions. You may merge and share merges of Open versions.
6. When sharing the allowed merges of Open versions, as well as finetunes of them, you must apply these same additional license terms.
7. Redistribution of Restricted versions is prohibited. They may only be obtained from official sources designated by the creator.
8. All use-based restrictions of the CreativeML Open RAIL++M license apply to SDXL versions and their derivatives. All use-based restrictions of the FLUX Non-Commercial License apply to Klein versions and their derivatives.
9. Any restrictions in these additional terms may be waived only with explicit written permission from the creator.
TLDR: This is basically the same license as before (just stated more clearly), so nothing changes for the Pony, XL, Photo, Insta, Lust and ZT versions of Big Love. However, restrictions were added for Ultra, Hyper, Klein, Zia, Zuna, Eryn, Gwen, Cat, KreaEdit and KreaLife versions (no merging, no redistribution). The "Share merges" condition below the license on the right hand side was only deactivated because of the restricted versions. Merging is still allowed for the open versions.
Many thanks to the creators of SDXL, Z, Qwen, Flux klein, Pony, bigAsp and Lustify for making their wonderful models available. Big thanks to RaymondLuxuryYacht for allowing me to train on his fabulous images.
Description
Please note: The Gwen versions of Big Love are pay-only and special license conditions apply. See description!
Big Love Gwen1 is a finetune of Qwen Edit 2511 and can do NSFW image editing. It produces more realistic and sharp images with better skin texture & genitals than other Qwen checkpoints/loras. Txt2img is less reliable, but generates nice results too.
Big Love Gwen1 allows commercial usage without additional fees (if no auto-generation involved) unlike Big Love Klein. With its better anatomy it is easier to get good editing results. Gwen1 is 50% faster than Klein at comparable settings without memory limitations.
The fp8 mixed version is for 16+ GB VRAM (highest quality), the nf4 version is for 12 and 16 GB VRAM (25% faster), the GGUF Q5_K_M version is for 16 GB VRAM (softest) and the nvfp4 version requires 24+ GB VRAM (on RTX 5090 2-3x faster, otherwise 2x slower, lower quality than fp8 mixed, less saturation, textured).
It is recommended to use ComfyUI. The Gwen1 workflows offer a skin enhance feature that is not available in Forge Neo. Move the Gwen1 model file into the diffusion_model sub folder of the models folder of ComfyUI, qwen_2.5_vl_7b_fp8_scaled.safetensors into the text_encoder sub folder and qwen_image_vae.safetensors into the vae sub folder.
For training a lora read here.
FAQ
Comments (62)
Wanted to especially thank you for the amazing Klein2 model! 🙏 It's completely insane and works like a charm! Best checkpoint i spent money on.
Also wanted to ask, will there be more updates on klein models?
For Forge Neo and BigLoveZT3, these settings are what I currently have best luck with:
Steps: 8, Sampler: Euler, Schedule type: Normal, CFG scale: 1, Shift: 5.5, Seed: 657451417, Size: 768x1408, Model hash: 1816c64b2a, Model: bigLove_zt3, Denoising strength: 0.3, Clip skip: 2, RNG: CPU, Hires Module 1: Use same choices, Hires CFG Scale: 1, Hires upscale: 1.55, Hires steps: 8, Hires upscaler: zImage4XUPSCALERBy_zit, Version: neo, Module 1: ae, Module 2: huihui-qwen3-4b-abliterated-v2-q8_0
That might change as I test more, but of the recommendations, that one worked best for both sharpness, quality and realism of the image.
Klein 2 model well worth the $10. Wonderful work with great fidelity.
For anyone else not seeing anything but a $15 subscription option on fanvue on any of the 6 images, disable uBlock. It's blocking something on the site related to following users, which you need to do first to see the six images (models) and their individual purchase options and prices.
Thanks for letting us know! Never heard about uBlock. Fanvue is a bit "special" as it only allows doing posts for follower. Why they are only accessible after following me there.
New biglove model! yayyy!
Opening fridge happy and closing it meme
Hi Subtle,
instead of Zuna I will stick to Klein since the edit capabilities are just too good.
However, I now tried to buy your Gwen checkpoint but sadly it seems like Fanvue requires credit card information.
On Tensor I can only see the fp8 mixed which would probably be too much for my GPU.
Any idea?
Nf4 for 12+ GB VRAM is now on Tensor Art. The others will follow soon. But I need to upload fp8 too as their generator does not support fp8 mixed. fp8 mixed can run on 12 GB VRAM too, but takes a lot longer.
@SubtleShader ok I used applepay and I am still not getting access. JFC why is this so complicated -.-
It's listed under "models bought" 3 times now as I thought it simply did not work the first 2 times. So I probably bought it 3 times now with 0 ways to download it lol
@SaburoDio Sorry to hear. Tensor Art can be a nuissance with payment.Better to use Fanvue. If your 3 orders did not go through now they are likely declined. Best wait a bit and try Fanvue.
@SubtleShader Tensor worked for me, thanks as always! I learned that the gguf would be best for my 16gb vram 4080 but the fp8_mixed will work also, right? I assume the fp8_m would offer better quality though so what's the rough dimension of "lot longer"? like 2x or 20x? Any idea?
@clairevalentine646 One guy with a 5060 ti (16 GB VRAM) said that fp8 mixed is faster than GGUF, which is surprising. So try fp8 mixed as it has the best quality. In my tests nf4 had better quality than GGUF despite smaller size. Let me know your findings.
@SubtleShader I get around 25-30s total for editing a 1080p img. skin enh on, upscale off and 3-4s/it that is.
@clairevalentine646 Sounds good. Which version? fp8 mixed? nf4?
@SubtleShader fp8 mixed, comfyui
@clairevalentine646 That is good. Takes around 10 seconds on a 5090. nf4 should be faster on the 5080.
@SubtleShader indeed. resemblance/id preservation is a bit subpar for me though, dunno why. Can the fp8 mixed be trained on with AI-T, or should I use full fp8 for that?
@clairevalentine646 The mixed format is not supported by trainers as far as I know. fp8 mixed could be converted to bf16 but too big to train on. Training on fp8 should be best. I still need to provide a training version as the released versions are all distilled. Have to test first what works best. I will likely recommend OneTrainer as it allows training with less VRAM than AI-Toolkit.
The face consistency can be improved with a lora. Have to look it up and try myself.
@SubtleShader nice. thanks for allthe effort! One thing I just noticed, with fp8-mixed the edited - and only those - areas get a strange grainy to whirl or block shaped texture. At least with the regular workflow from your examples. I'll try one of the other versions later to see, if it can be reproduced...
How would you compare Gwen vs klein for editing purposes ? I read the description
I did not test both against each other yet. Gwen1 was a huge amount of work so I did not find the time so far. But here are my impressions:
Gwen:
+ Better anatomy
+ More creative posing & perspectives
+ Better prompt following
+ Lovely faces in txt2img
+ Better license
Klein:
+ Less VRAM needed
+ Better skin texture/photorealism
+ Sharper images
+ Better at sex scenes
+ Better at upscaling
I think having 2-3 image editing models rather than one makes sense. Some things will always work better with one or the other. And you can feed the output of one model to the other.
Plan for Zia2?
Yep. My plan is to makes it as good at NSFW as Zuna1.
Hi Subtle, I've just purchase both Klein and Qwen versions. Is there any recommendation when to use one or another? Which one is more consistent with preserving facial features? Thanks
I will test both this week against each other to see what I can improve in future. I think both preserve facial features similarly good. Some faces work better with one or the other. Sometimes Gwen1 makes a face look even better or more realistic than the original one, which I have never seen happen with Klein.
@SubtleShader from my tests to now, Gwen seems to be best for editing parts of the image, changing clothes, fixing anatomy (before second pass with Ultra) and subtle variations on same image. Klein seems best to create new scenes based on reference subjects, and preserving face consistency on new scenes seems to be better. Im still testing, but I guess both models are complementary, with a final inpaint pass with Ultra or Photo, to make some anatomy more realistic.
thanks for working on a qwen one
Big Love Gwen1 fp8 mixed with 16 GB VRAM
Two people confirmed that it works fine. Let me know. Especially if the nf4 version is not a lot faster. Thanks!
would buy with buzz if you had a bf16 or fp16 version available.
I can upload it but will take a while. Remind me afterwards.
@SubtleShader Got busy with a project, came back and see you've changed this to gen only. Is it for sale at tensor art or ? Also curious how it compares to firered edit or did you train on that? FireRed1 qwen edit is very good.
@EricRollei21 Yes, still available at Fanvue. A FireRed based version would be a possibility, but I just did some tests: Qwen Edit is a lot better with posing, prompt adherence and produces less soft images. So I'll pass on FireRed.
@SubtleShader Hmm, can't agree. I use FireRed1 edit for almost everything now. It's better imho than qwen edit.
@EricRollei21 What type of editing do you do?
I love all of your models, I have bought all of the new ones. Would it be possible to add gestures like flipping off the camera/viewer as a concept?
I trained the middlefinger gesture into Big Love Photo. Z can already do it. Some of the other models might too. Will see if I can do more concepts in this direction.
I'm currently only training special new concepts into SDXL, because the newer models still need to learn more basic NSFW stuff.
How to buy a model on Fanvue? One post one model? Post titles are closed, dont see what model I buying. Last time I bought it on whop, now its closed.
You need to follow me to see which is which. Sorry, I'm not making the rules. Fanvue wants that.
Try to train on Firered model of qwen, its much better with textures and hires.
Thanks! Will take a look. Some say it is worse, some praise it.
Much appreciate the Gwen model. I bought it and it's promising - however I'd love a version without the lightning lora merged . I find myself often finetuning lightning lora power in my multi step workflows but with it hardcoded that's impossible. Could you add a non-lightning variant please?
Will add it when uploading a training version. Still need to test it though.
@SubtleShader awesome. appreciate it. by 'training version' you mean a bf16?
@QualityControl Whatever works in AI-Toolkit and OneTrainer. Bf16 likely.
@SubtleShader oh a version we can train in AI toolkit without lightning would be amazing
@SubtleShader great work buddy, got it off fanvue. any eta as to when you will be uploading the trainable version? no rush
@HashTagSendNudes Just uploaded. Instructions: https://civitai.red/models/897413/big-love?dialog=commentThread&commentId=1196689
Hello, how should I properly tune onetrainer for a finetune of Photo6?
I followed your section "Training a (character) lora" but I do not have good results at all. My understanding was that training a finetune and then extracting the lora from it is best yes? I am also unsure what you meant by "add tags on the Tools tab", did you mean captions?
Could you perhaps give us either the settings that you use or a config we can load in onetrainer please?
That would be much appreciated, thank you :)
Bad character loras can have various reasons. Martin Bosgra wrote an article about extracting a lora from a finetuned checkpoint. Follow his instructions if you want that.
Tags or captions is more or less the same term apart from tags being shorter than captions, e.g. 1-2 words vs 5-12 words.
The presets of the latest OneTrainer version are quite good. I have seen various people trying to "improve" them and it ended in bad results and wasted energy.
@SubtleShader Hello, never mind I'm just stupid.
I just had to train an SDXL Lora as is instead of finetuning. Just a lora as is worked extremely well, very fast too. Had no tags, instead I used 5000 reg images from SECourses and also "single text file as caption" for my training images with my custom keyword inside of the file and it worked wonders.
Now I'm eagerly awaiting your new qwen model!
I'm trying to use Eryn1 with the default showcase workflow. I'm getting a CLIPLoader error stating Llama2 and size mismatch for a long list of errors. I've done a full update and reload, but I haven't been able to fix this. Any advice?
This usually means that you have to update your ComfyUI. Ernie is not supported by older versions of ComfyUI as it was released rather recent.
Was in the midst of downloading -Big Love Photo 6- checkpoint and it failed - and now all I get is 'file not found'. Do others have the same problem? 'Big Love' models seem all to suddenly produce 'file not found'
Civitai problems as usual. Yesterday the website was extremely slow. Try again later. These things are temporary.
Just writing to CONGRATULATE YOU FOR THE İNSANE GWEN MODEL ! CRAZY !
Got Gwen1 and new Ultra - nice :) But with Gwen1: Are there tricks to get the reference face be more present in the workflow? I managed to get versions with 2 faces work fine using a lot of prompting, but often the face is not really matching, so I was wondering if you had some tricks up your sleeve (node-tweaks, adding a certain new node etc). Thnx
There are some loras that improve face consistency, but did not test them yet. See
https://civitai.red/models/2076212/change-head-and-face-lora-for-qwenedit2509
https://civitai.com/models/2094349/qwen-image-edit-f2p
https://huggingface.co/landon2022/F2P
Lora Training With Gwen
Training on Gwen is a bit more demanding than usual. To make it work you need:
1. AI-Toolkit
2. 32 GB VRAM (RTX 5090 or better)
3. Probably 64 GB RAM (Not sure if 32 GB RAM is just slower or does not work)
4. 100+ GB free space on your SSD
5. Download BigLoveGwen_diffusers.zip under Optional Files and unzip it somewhere.
6. Download ai-toolkit_mod_qwenedit.zip under Optional Files and replace these 2 files in the ai-toolkit sub folders with the ones from the zip file:
toolkit\dataloader_mixins.py extensions_built_in\diffusion_models\qwen_image\qwen_image_edit_plus.py
If you do not apply my AI-Toolkit mod, you need at least 48 GB VRAM and have to set a control dataset, which can be either the target dataset again, a folder of black images or a single image replicated for each of your training images. I did not test this, so it might be less effective than using the mod.
Mandatory AI-Toolkit Settings:
Model Architecture: Qwen-Image-Edit 2511
Name or Path: Path where you unzipped BigLoveGwen1_diffusers.zip
Low RAM: True
Quantization Transformer: float8 (default)
Quantization Text Encoder: float8 (default)
Cache Text Embedding: True
Cache Latents: True
Resolutions: 1024 (or only 512 if you want 4x faster training)
Target Dataset: Your training images
Control Dataset 1-3: Leave empty
Good luck with training!
Hi Subtle,
How do you train biglove zit3 for a face/model lora? You talk about the full model on description which I got a bit confused since I cant find any. Thanks! (using ai-toolkit!)
Shit I found it in discord! LOL https://civitai.com/models/897413/big-love?modelVersionId=2768854&dialog=commentThread&commentId=1117342
@dxjaymz Easier to just look in the description above 😁



















