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klein-9b/lora/NippleDiffusion - Flux2.Klein/extra_data-vid_2646182/model_dict-mid_2331032-vid_2646182.json

@@ -1,7 +1,7 @@
 {
   "id": 2331032,
   "name": "NippleDiffusion - Flux2.Klein",
-  "description": "<p>Now your Flux2 Klein can generate breasts. Not good with vaginas.</p><p>I may release some individual breasts loras like I did for Flux1.Dev. Let's see....</p><hr /><p>I was tired of other LoRAs without the areolas textures and details. Most of the nipples I got until now using Flux was some soulless plain areolas without the depth it requires.</p><p>Then I curated a mid-size dataset with the best breasts and areolas I could find today in the internet.</p><p><strong>Types of breasts trained</strong>: (<em>Not trigger words, but the types of images used to train</em>)</p><ul><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>big areolas</strong></span> - <em>Rounded medium to big areola size</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>dark nipples</strong></span> - <em>Dark nipples with more contrast to the natural skin</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>pale nipples</strong></span> - <em>Pale nipples that appears slightly</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>big nipples</strong></span> - <em>Nipples that you can bite easily</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>puffy nipples</strong></span> - <em>Small breasts with the tip of them covered with a dense nipple</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>saggy breasts </strong></span>- <em>breasts hanging a bit due to the gravity</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>small areolas</strong></span> - <em>Areolas with a small radius</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>veiny areolas</strong></span> - <em>Veins appearing under the skin</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>banana tits</strong></span> - <em>Similar to puffy, but focused on breast shape instead of nipples only</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>silicone tits</strong></span> - <em>The spheres from the 90s. It focuses on shape</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>empty tits</strong></span> - <em>Similar to saggy, but empty</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>flat tits</strong></span> - <em>Flat chested woman</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>oval areolas</strong></span><span style=\"color:rgb(253, 126, 20)\"><em> </em></span><em>- When it's cold, the areola shape may change to oval. Good texture</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>bumpy areolas</strong></span><em> - When it's cold, the areola texture becomes bumpy. Good texture</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>wrinkled areolas</strong></span><em> - When it's cold big areolas becomes wrinkled! Good texture</em></p></li></ul><p><strong>Flux does what it wants </strong>LOL.<span style=\"color:rgb(190, 75, 219)\"> <strong>I trained different concepts, but flux does not always follow them</strong></span>. <span style=\"color:rgb(190, 75, 219)\"><strong>Flux seems doing a breast based on the overall girl appearance</strong></span>, but it's possible to achieve using inpainting and some prompt engineering.</p><p>Bonus that I added in case the full body appears, to have something right down there:</p><ul><li><p><span style=\"color:rgb(190, 75, 219)\"><strong>hairy pussy</strong></span> - <em>hairy pussy of a woman standing</em></p></li><li><p><span style=\"color:rgb(190, 75, 219)\"><strong>shaved pussy </strong></span>- <em>shaved pussy of a woman standing</em></p></li></ul><p></p>",
+  "description": "<p>Now your Flux2 Klein can generate breasts. Not good with vaginas.</p><p><strong>NOW WE HAVE </strong><span style=\"color:rgb(250, 82, 82)\"><strong>BANANA|TORPEDO and SAGGY TITS</strong></span><strong>!!! See the stand-alone lora file version at the top</strong></p><hr /><p>I was tired of other LoRAs without the areolas textures and details. Most of the nipples I got until now using Flux was some soulless plain areolas without the depth it requires.</p><p>Then I curated a mid-size dataset with the best breasts and areolas I could find today in the internet.</p><hr /><p><strong>Stand-alone lora files:</strong></p><ul><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>long nipples</strong></span> - <em>Nipples that you can bite easily</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>puffy nipples</strong></span> - <em>Small breasts with the tip of them covered with a dense nipple</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>veiny areolas</strong></span> - <em>Veins appearing under the skin</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>dark nipples</strong></span> - <em>Dark nipples with more contrast to the natural skin</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>banana tits</strong></span> - <em>Similar to puffy, but focused on breast shape instead of nipples only</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>saggy breasts </strong></span>- <em>breasts hanging a bit due to the gravity</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>empty tits</strong></span> - <em>Similar to saggy, but empty</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>flat tits</strong></span> - <em>Flat chested woman</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>oval areolas</strong></span><span style=\"color:rgb(253, 126, 20)\"><em> </em></span><em>- When it's cold, the areola shape may change to oval. Good texture</em></p></li></ul><hr /><p><strong>Types of breasts trained on general lora</strong>: (<em>Not trigger words, but the types of images used to train</em>)</p><ul><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>big areolas</strong></span> - <em>Rounded medium to big areola size</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>dark nipples</strong></span> - <em>Dark nipples with more contrast to the natural skin</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>pale nipples</strong></span> - <em>Pale nipples that appears slightly</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>big nipples</strong></span> - <em>Nipples that you can bite easily</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>puffy nipples</strong></span> - <em>Small breasts with the tip of them covered with a dense nipple</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>saggy breasts </strong></span>- <em>breasts hanging a bit due to the gravity</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>small areolas</strong></span> - <em>Areolas with a small radius</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>veiny areolas</strong></span> - <em>Veins appearing under the skin</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>banana tits</strong></span> - <em>Similar to puffy, but focused on breast shape instead of nipples only</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>silicone tits</strong></span> - <em>The spheres from the 90s. It focuses on shape</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>empty tits</strong></span> - <em>Similar to saggy, but empty</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>flat tits</strong></span> - <em>Flat chested woman</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>oval areolas</strong></span><span style=\"color:rgb(253, 126, 20)\"><em> </em></span><em>- When it's cold, the areola shape may change to oval. Good texture</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>bumpy areolas</strong></span><em> - When it's cold, the areola texture becomes bumpy. Good texture</em></p></li><li><p><span style=\"color:rgb(250, 82, 82)\"><strong>wrinkled areolas</strong></span><em> - When it's cold big areolas becomes wrinkled! Good texture</em></p></li></ul><hr /><p><strong>Flux does what it wants </strong>LOL.<span style=\"color:rgb(190, 75, 219)\"> <strong>I trained different concepts, but flux does not always follow them</strong></span>. <span style=\"color:rgb(190, 75, 219)\"><strong>Flux seems doing a breast based on the overall girl appearance</strong></span>, but it's possible to achieve using inpainting and some prompt engineering.</p><p>Bonus that I added in case the full body appears, to have something right down there:</p><ul><li><p><span style=\"color:rgb(190, 75, 219)\"><strong>hairy pussy</strong></span> - <em>hairy pussy of a woman standing</em></p></li><li><p><span style=\"color:rgb(190, 75, 219)\"><strong>shaved pussy </strong></span>- <em>shaved pussy of a woman standing</em></p></li></ul><p>You can use multiple loras, but the image may degrade... It's just how it works sadly.</p><p></p>",
   "allowNoCredit": true,
   "allowCommercialUse": "{Image,RentCivit,Rent,Sell}",
   "allowDerivatives": true,
@@ -15,13 +15,13 @@
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   "userId": 70294,
   "cosmetic": null,
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   "creator": {
     "username": "Skullkid",
@@ -41,7 +41,7 @@
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-      "name": "v2.0 [9B] - General Lora",
+      "name": "💚 General [9B] v2",
       "baseModel": "Flux.2 Klein 9B",
       "baseModelType": "Standard",
       "createdAt": "2026-01-31T08:21:29.502Z",
@@ -50,10 +50,10 @@
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       "description": "<p>Improved model overall</p>",
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+        "long hanging saggy breasts"
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klein-9b/lora/Sex, Nudes, Other Fun Stuff (SNOFS)/extra_data-vid_2695876/model_dict-mid_1972981-vid_2695876.json

@@ -0,0 +1,1878 @@
+{
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+  "name": "Sex, Nudes, Other Fun Stuff (SNOFS)",
+  "description": "<h2 id=\"general-information:\">General Information:</h2><p><em>SNOFS was trained on natural language, not tags. It will work best if you use full sentences to describe what you want.</em></p><p>For all of those clamoring for me to train on other models, you can help make that happen by joining the Patreon link in my profile. The money will go towards renting cloud GPU time. If you do subscribe, tell me what model you'd like me to focus on. I'll still continue to train further on this version as it could go further.</p><p>By the way, if anyone out there needs an expert in fine tuning text-to-image models (especially one that's also a software engineer), reach out to me. I'm currently looking for employment.</p><p></p><p>Here's a list of some of the terms that work well:</p><ul><li><p>anus</p></li><li><p>blowjob</p></li><li><p>deepthroat</p></li><li><p>braless</p></li><li><p>cowgirl position</p></li><li><p>cum</p></li><li><p>cunnilingus (be specific and maybe put kissing in the negative prompt)</p></li><li><p>deepthroat</p></li><li><p>dildo</p></li><li><p>doggystyle position</p></li><li><p>fingering</p></li><li><p>hand in panties</p></li><li><p>handjob</p></li><li><p>hitachi magic wand</p></li><li><p>implied blowjob</p></li><li><p>ipcam / nightvision ipcam</p></li><li><p>masturbating (might want to put penis in negative prompt, or specify what she's rubbing for women)</p></li><li><p>massage</p></li><li><p>missionary position</p></li><li><p>naked, nude, etc.</p></li><li><p>penis</p></li><li><p>pregnant (and can specify trimester)</p></li><li><p>prone position</p></li><li><p>reverse cowgirl position</p></li><li><p>sex</p></li><li><p>sheer</p></li><li><p>snapchat (and caption/text/etc)</p></li><li><p>selfie (and mirror selfie)</p></li><li><p>spooning position</p></li><li><p>strap-on dildo</p></li><li><p>tentacles</p></li><li><p>licking testicles</p></li><li><p>undressing</p></li><li><p>vagina</p></li><li><p>wet shirt</p></li></ul><p>Depending on the version, the following might kind of work:</p><ul><li><p>anal sex</p></li><li><p>anilingus</p></li></ul><p></p><h3 id=\"flux-2-klein-9b-v1.1:\">Flux 2 Klein 9b V1.1:</h3><p>Additional training means far less body horror, even on the distilled version (but, you know, still some there). When using the distilled version of the model try playing around with more steps, adding a little cfg, etc.</p><p></p><h3 id=\"flux-2-klein-9b-v1:\">Flux 2 Klein 9b V1:</h3><p>Flux 2 Klein's awesome VAE means it picks up fine details incredibly well. While it still needs more training, I have some other stuff to train in the meantime so I thought it was worth it to push this out now as it can do some things incredibly well. Expect some body horror, <em>especially if you use it with the distilled version of the model for text-to-image</em>. I found that perhaps using more steps than 4 was helpful with the distilled version, but I also didn't try it much. Using this with the base model has far less anatomy issues. I expect them both to improve further with more training.</p><p>Right now, for text-to-image I recommend the base model. For editing, I recommend the distilled model. Note that SNOFS wasn't specifically trained on any image pairs for editing.</p><p></p><p></p><p><strong>Training details</strong> (skip to the version 1.3 details below if you just want to know what this model can at least somewhat do right now):</p><p>I trained this as a factor 4 lokr using AI Toolkit this time. I used AI-Toolkit because when I started the training the other options had issues with their lycoris output and ComfyUI.</p><p></p><p>I think my starting learning rate was way too high at 1e-4 with an effective batch size of 4-6 or so. I quickly decreased it but it was perhaps still too high starting at 5e-5. I'm running a different training run at 1e-5 right now and it's still learning quite quickly. I might try to further train this at a very low LR and see what happens instead of starting fresh. Note: this is probably largely because of my large lokr size. I wanted to ensure I had \"room\" for all of the concepts but it can make things spicy.</p><p></p><p>I think the main issue people are coming into with training both this and Z-Image are what timesteps you train on. This was mostly trained on a high shift value of 3-5 as in inference Flux 2 Klein stays above the 800 timestep mark for most of the generation and maybe does 1 step out of 50 at below 200. I found I needed to test as I went and see where the generations went wrong and try to adjust on the fly.</p><p></p><h3 id=\"version-1.3:\">Version 1.3:</h3><p>Further training to further refine things. This <em>might</em> be the last version; I wasn't really making this for myself and I'm guessing the community wants me to make something for Z-Image. I'll at least try that out once the base model is out.</p><p>Note that the list is not exhaustive at all. It was trained on natural language (and that's how you should prompt!), so many concepts are in there.</p><p></p><h3 id=\"version-1.2:\">Version 1.2:</h3><p>Further training, expanded the dataset even more.</p><p></p><p>Also, I see a lot of people mixing this with other NSFW general loras. I'd recommend you try it by itself first.</p><p></p><p>Note: While you can use the lightning lora with this, keep in mind it won't lead to the best results. It's great for testing prompts, but it tends to mess with anatomy, smooth out texture, and lead to less variation on the same prompt.</p><p></p><h3 id=\"version-1:\">Version 1:</h3><p></p><p>This past weekend I was gone. I decided to let my 5090 chug along making a lokr for Qwen on ~5,000 hand fixed captions on sex, nudes, and other fun stuff of hand picked images with hand removed watermarks. I wasn't expecting it to get so good so quickly, so I did a few more night's worth of training. I'll do some additional training at some point here but it's already good enough to play around with.</p><p>It can do basic sex positions, blowjobs, cum, selfies, dildos, snapchat selfies with captions, etc. Female genitals are still a bit hit and miss, male genitals aren't bad. With it being a lokr and it being trained on so many images it's wildly flexible and can be used with perfect likeness of other loras.</p><p>Note that sometimes it'll do the wrong sex position even if you name it, and I'm unsure why as the captions have no errors. It will perhaps clear up a bit with more training.</p><p>I used Musubi Tuner and it was a heck of time getting it to train a lokr. I had to use another lycoris library for it (which is somewhere in the issues on the github page, IIRC), but it's possible the main one has Qwen support by now. Here are my training settings, though note that I reduced my LR over time and I also started with sigmoid timestep sampling. I was training at 640x640 and 1328x1328 buckets:<br /><br />accelerate launch --num_cpu_threads_per_process 1 --mixed_precision bf16 src\\musubi_tuner\\qwen_image_train_<a target=\"_blank\" rel=\"ugc\" href=\"http://network.py\">network.py</a> `</p><p>--dit Q:\\AI\\Models\\DiffusionModels\\qwen_image_bf16.safetensors `</p><p>--vae Q:\\AI\\Models\\VAE\\qwen_vae_for_training.safetensors `</p><p>--text_encoder Q:\\AI\\Models\\CLIP\\qwen_2.5_vl_7b.safetensors `</p><p>--dataset_config S:\\AI\\Musubi\\datasetWoman.toml `</p><p>--sdpa --mixed_precision bf16 `</p><p>--gradient_accumulation_steps 4 `</p><p>--timestep_sampling qinglong_qwen `</p><p>--optimizer_type adamw8bit `</p><p>--learning_rate 3e-4 --lr_scheduler linear --lr_scheduler_min_lr_ratio=1e-5 --lr_warmup_steps 150 `</p><p>--blocks_to_swap 25 `</p><p>--gradient_checkpointing --gradient_checkpointing_cpu_offload --max_data_loader_n_workers 2 --persistent_data_loader_workers `</p><p>--network_module lycoris.kohya `</p><p>--network_args \"algo=lokr\" \"factor=10\" \"bypass_mode=False\" \"use_fnmatch=True\" \"target_module=Linear\" `</p><p>\"target_name=unet.transformer_blocks.*.<a target=\"_blank\" rel=\"ugc\" href=\"http://attn.to\">attn.to</a>_q\" `</p><p>\"target_name=unet.transformer_blocks.*.<a target=\"_blank\" rel=\"ugc\" href=\"http://attn.to\">attn.to</a>_k\" `</p><p>\"target_name=unet.transformer_blocks.*.<a target=\"_blank\" rel=\"ugc\" href=\"http://attn.to\">attn.to</a>_v\" `</p><p>\"target_name=unet.transformer_blocks.*.<a target=\"_blank\" rel=\"ugc\" href=\"http://attn.to\">attn.to</a>_out.0\" `</p><p>\"target_name=unet.transformer_blocks.*.attn.add_q_proj\" `</p><p>\"target_name=unet.transformer_blocks.*.attn.add_k_proj\" `</p><p>\"target_name=unet.transformer_blocks.*.attn.add_v_proj\" `</p><p>\"target_name=unet.transformer_blocks.*.<a target=\"_blank\" rel=\"ugc\" href=\"http://attn.to\">attn.to</a>_add_out\" `</p><p>\"target_name=unet.transformer_blocks.*.img_<a target=\"_blank\" rel=\"ugc\" href=\"http://mlp.net\">mlp.net</a>.0.proj\" `</p><p>\"target_name=unet.transformer_blocks.*.img_<a target=\"_blank\" rel=\"ugc\" href=\"http://mlp.net\">mlp.net</a>.2\" `</p><p>--network_dim 1000000000 `</p><p>--save_every_n_steps 250 --max_train_epochs 10--logging_dir=logs `</p><p>--output_dir Q:/AI/Models/Trained/Loras/Musubi/QwenWoman --output_name WomanGirls<br /></p>",
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