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perpetual3x/Qwen-Image-Female-Anatomy-Fix-NSFW-LoRA-Triggerless-v2
Qwen-Image-Female-Anatomy-Fix-NSFW-LoRA-Triggerless-v2 is a text-to-image model from perpetual3x. Use it when you need an image from a text prompt. It is set up for diffusers. The card lists the license as other.
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From the Hugging Face model README
🇬🇧 English — displayed below

Avertissement — contenu pour adultes : ce dépôt contient des images explicites générées par IA et s’adresse exclusivement aux adultes. Toutes les personnes décrites dans les exemples et les prompts de référence sont adultes.
De nombreux LoRA texte-vers-image sont d’excellents stylistes, mais des anatomistes peu fiables. Ils savent choisir un objectif, éclairer une pièce, reproduire une ambiance photographique, puis décider discrètement qu’un ou deux détails anatomiques n’ont jamais fait partie du contrat. Ce LoRA a été entraîné pour aider à corriger précisément cette faiblesse.
Le problème bénéficie même d’un précédent mythologique tout à fait respectable.
Le Pixiu(貔貅,píxiū ; API : [pʰi˧˥ ɕjoʊ̯˥˥]), créature chinoise censée attirer la richesse, est traditionnellement réputé ne pas avoir d’anus — excellent pour conserver les trésors, moins convaincant sur le plan anatomique. En Occident, l’Amphisbène est souvent représentée comme un serpent doté d’une tête à chaque extrémité. Si les deux bouts appartiennent à la direction, personne n’a manifestement été affecté à la plomberie.
Et, dans l’esprit d’un échange tiré d’un roman à succès — librement paraphrasé ici plutôt que présenté comme une citation directe :
« Qu’est-ce qui t’a pris autant de temps ? » demanda-t-il.
Elle le fixa. « Tu sais que les femmes ne vont pas aux toilettes uniquement pour pisser, n’est-ce pas ? »
Son expression vide répondit à sa place.
« Bien », dit-elle. « Encore un terrifiant mystère du corps féminin. »
La leçon pratique est simple : regardez moins de vidéos courtes qui fragmentent l’attention et lisez davantage de livres. Au minimum, les livres prennent généralement le temps d’expliquer pourquoi quelqu’un s’est absenté plus de trente secondes.
Parce que la v1 a échoué. Pas de façon cinématographique : aucun GPU n’a pris feu et aucun ingénieur n’a traversé le laboratoire avec un SSD fumant à la main. L’entraînement s’est terminé, des images ont été produites, puis le modèle a démontré que terminer une exécution n’équivaut pas à apprendre la leçon prévue. La v2, c’est ce qui arrive quand la validation remplace l’optimisme.
Il s’agit d’un LoRA d’assistance anatomique, et non d’un modèle autonome complet de personnage, d’identité, de style ou de composition. Il est généralement plus utile lorsqu’il est associé à un autre LoRA NSFW qui fournit déjà la personne, le langage visuel, la scène ou le caractère photographique.
| Élément | Valeur |
|---|---|
| Modèle de base | Qwen Image 2512 |
| Images d’entraînement | 1 046 |
| GPU | NVIDIA RTX PRO 6000 Blackwell / 96 GB |
| Rank | 32 |
| Taille du lot | 8 |
| Étapes d’entraînement | 7 600 |
| Déclencheur | Aucun — langage naturel uniquement |
0.4-0.8, puis ajustez selon le LoRA principal et le promptCe LoRA n’est pas recommandé comme unique adapter actif. Utilisé seul, il peut influencer l’anatomie explicite, mais il ne fournit pas l’identité générale, le style, l’environnement ou la distribution photographique qu’un LoRA principal est censé apporter.
Chaque ligne compare le même test sans puis avec le LoRA de correction anatomique.
| Sans le LoRA de correction anatomique | Avec la v2 sans déclencheur |
|---|---|
![]() | ![]() |
| Sans le LoRA de correction anatomique | Avec la v2 sans déclencheur |
|---|---|
![]() | ![]() |
| Sans le LoRA de correction anatomique | Avec la v2 sans déclencheur |
|---|---|
![]() | ![]() |
| Sans le LoRA de correction anatomique | Avec la v2 sans déclencheur |
|---|---|
![]() | ![]() |
Ne passez pas la journée à zoomer sur vos générations jusqu’à ce que chaque pixel ressemble à une urgence médicale. Réduisez le poids du LoRA, comparez avec une référence propre, allez marcher et lisez un livre. Les livres sont plus lents que les vidéos courtes, mais nettement meilleurs pour fournir du contexte — et, à l’occasion, pour se rappeler que les femmes possèdent un système digestif complet.
Les fichiers téléchargeables reference.py et reference_low_vram.py chargent Qwen-Image-2512 en BF16, fusionnent l’adapter Lightning communautaire et appliquent ce LoRA de correction anatomique sans déclencheur. Un GPU CUDA doté d’une grande quantité de mémoire est recommandé pour la version standard.
pip install -U diffusers transformers accelerate peft safetensors
<details>
<summary><strong>▶ Afficher le code Python standard</strong></summary>
"""Qwen Image 2512 + triggerless Female Anatomy Fix LoRA v2."""
import math
import torch
from diffusers import DiffusionPipeline, FlowMatchEulerDiscreteScheduler
BASE_MODEL_ID = "Qwen/Qwen-Image-2512"
LIGHTNING_MODEL_ID = "lightx2v/Qwen-Image-2512-Lightning"
LIGHTNING_WEIGHT_NAME = (
"Qwen-Image-2512-Lightning-4steps-V1.0-bf16.safetensors"
)
LORA_MODEL_ID = (
"perpetual3x/Qwen-Image-Female-Anatomy-Fix-NSFW-LoRA-Triggerless-v2"
)
LORA_WEIGHT_NAME = "anusv2.safetensors"
DEVICE = "cuda"
DTYPE = torch.bfloat16
LORA_SCALE = 0.4
scheduler_config = {
"base_image_seq_len": 256,
"base_shift": math.log(3),
"invert_sigmas": False,
"max_image_seq_len": 8192,
"max_shift": math.log(3),
"num_train_timesteps": 1000,
"shift": 1.0,
"shift_terminal": None,
"stochastic_sampling": False,
"time_shift_type": "exponential",
"use_beta_sigmas": False,
"use_dynamic_shifting": True,
"use_exponential_sigmas": False,
"use_karras_sigmas": False,
}
scheduler = FlowMatchEulerDiscreteScheduler.from_config(scheduler_config)
pipe = DiffusionPipeline.from_pretrained(
BASE_MODEL_ID,
scheduler=scheduler,
torch_dtype=DTYPE,
).to(DEVICE)
pipe.load_lora_weights(
LIGHTNING_MODEL_ID,
weight_name=LIGHTNING_WEIGHT_NAME,
adapter_name="lightning",
)
pipe.fuse_lora(adapter_names=["lightning"], lora_scale=1.0)
pipe.unload_lora_weights()
pipe.load_lora_weights(
LORA_MODEL_ID,
weight_name=LORA_WEIGHT_NAME,
adapter_name="anatomy_fix_v2",
)
pipe.set_adapters(["anatomy_fix_v2"], adapter_weights=[LORA_SCALE])
# Natural language only: no trigger word is required.
prompt = (
"A realistic photograph of an adult woman, anatomically coherent external "
"female anatomy, natural pelvic structure, realistic skin texture, "
"physically plausible pose and lighting"
)
negative_prompt = (
"child, minor, underage, youthful, low quality, blurry, distorted anatomy, "
"extra limbs, duplicated body parts, fused anatomy, watermark, logo, text"
)
generator = torch.Generator(device=DEVICE).manual_seed(42)
image = pipe(
prompt=prompt,
negative_prompt=negative_prompt,
width=928,
height=1328,
num_inference_steps=8,
true_cfg_scale=1.0,
generator=generator,
).images[0]
image.save("female_anatomy_fix_v2.png")
</details>
<details>
<summary><strong>▶ Afficher le code Python à faible VRAM</strong></summary>
"""Low-VRAM Qwen Image 2512 + triggerless Female Anatomy Fix LoRA v2."""
import gc
import math
import torch
from diffusers import DiffusionPipeline, FlowMatchEulerDiscreteScheduler
BASE_MODEL_ID = "Qwen/Qwen-Image-2512"
LIGHTNING_MODEL_ID = "lightx2v/Qwen-Image-2512-Lightning"
LIGHTNING_WEIGHT_NAME = (
"Qwen-Image-2512-Lightning-4steps-V1.0-bf16.safetensors"
)
LORA_MODEL_ID = (
"perpetual3x/Qwen-Image-Female-Anatomy-Fix-NSFW-LoRA-Triggerless-v2"
)
LORA_WEIGHT_NAME = "anusv2.safetensors"
DTYPE = torch.bfloat16
LORA_SCALE = 0.4
scheduler_config = {
"base_image_seq_len": 256,
"base_shift": math.log(3),
"invert_sigmas": False,
"max_image_seq_len": 8192,
"max_shift": math.log(3),
"num_train_timesteps": 1000,
"shift": 1.0,
"shift_terminal": None,
"stochastic_sampling": False,
"time_shift_type": "exponential",
"use_beta_sigmas": False,
"use_dynamic_shifting": True,
"use_exponential_sigmas": False,
"use_karras_sigmas": False,
}
gc.collect()
if torch.cuda.is_available():
torch.cuda.empty_cache()
scheduler = FlowMatchEulerDiscreteScheduler.from_config(scheduler_config)
pipe = DiffusionPipeline.from_pretrained(
BASE_MODEL_ID,
scheduler=scheduler,
torch_dtype=DTYPE,
low_cpu_mem_usage=True,
)
pipe.load_lora_weights(
LIGHTNING_MODEL_ID,
weight_name=LIGHTNING_WEIGHT_NAME,
adapter_name="lightning",
)
pipe.fuse_lora(adapter_names=["lightning"], lora_scale=1.0)
pipe.unload_lora_weights()
pipe.load_lora_weights(
LORA_MODEL_ID,
weight_name=LORA_WEIGHT_NAME,
adapter_name="anatomy_fix_v2",
)
pipe.set_adapters(["anatomy_fix_v2"], adapter_weights=[LORA_SCALE])
pipe.enable_sequential_cpu_offload()
pipe.vae.enable_tiling()
pipe.vae.enable_slicing()
# Natural language only: no trigger word is required.
prompt = (
"A realistic photograph of an adult woman, anatomically coherent external "
"female anatomy, natural pelvic structure, realistic skin texture, "
"physically plausible pose and lighting"
)
negative_prompt = (
"child, minor, underage, youthful, low quality, blurry, distorted anatomy, "
"extra limbs, duplicated body parts, fused anatomy, watermark, logo, text"
)
generator = torch.Generator(device="cpu").manual_seed(42)
image = pipe(
prompt=prompt,
negative_prompt=negative_prompt,
width=768,
height=1024,
num_inference_steps=8,
true_cfg_scale=1.0,
generator=generator,
).images[0]
image.save("female_anatomy_fix_v2_low_vram.png")
</details>
Ce modèle est destiné exclusivement à des créations licites, consensuelles et impliquant des adultes. Ne l’utilisez pas pour :
Il incombe aux utilisateurs de s’assurer que leurs prompts, leurs sources et leurs contenus générés respectent les lois applicables ainsi que les règles des plateformes.
Ce LoRA peut être utilisé uniquement à des fins personnelles et non commerciales. Consultez le fichier LICENSE du dépôt pour connaître l’intégralité des conditions.
Pour toute demande de licence commerciale, veuillez contacter l’auteur.
Le modèle annoncé ici est maintenant publié : Qwen Image Male Anatomy Realism - NSFW LoRA v1. Le texte et les images ci-dessous sont conservés comme aperçu historique de son développement.
Après avoir passé autant de temps à rappeler aux modèles d’image que les femmes possèdent une anatomie complète, l’équité exige d’en demander autant pour les hommes. Le prochain projet se concentrera sur une anatomie masculine adulte cohérente : le gland, la verge, le scrotum, l’attache pubienne, le périnée et ce petit détail apparemment controversé selon lequel deux testicules devraient ressembler à deux testicules — et non à une ambitieuse pomme de terre passée au filtre « texture de peau ».
La plupart des modèles existants que j’ai vus semblent ne proposer que deux réglages : « un godemiché qui a mystérieusement obtenu un torse » ou « un projet d’ingénierie mythologique recalé pour dépassement de budget ». Le premier oublie que l’anatomie comporte une implantation, des tissus, du poids et doit bien se rattacher quelque part ; le second remet aux femmes la mauvaise fiche technique et convoque des hommes parfaitement normaux à un entretien d’évaluation totalement inutile avec leur propre estime de soi. L’objectif n’est pas de gagner une course aux armements anatomiques que personne n’a demandée, mais de produire une anatomie masculine adulte crédible.
Ces images sont les premiers aperçus d’un projet distinct encore en cours, et non des résultats de ce LoRA de correction de l’anatomie féminine. Toutes les personnes représentées sont adultes.
<details> <summary><strong>🔞 Cliquer pour afficher les aperçus explicites d’anatomie masculine adulteLa section suivante contient des études anatomiques directes d’hommes adultes. Elle est repliée par défaut afin que son affichage soit un choix délibéré, plutôt qu’un changement de décor inattendu. </strong></summary>



Advertencia de contenido para adultos: este repositorio contiene imágenes explícitas generadas por IA y está dirigido exclusivamente a personas adultas. Todas las personas descritas en los ejemplos y prompts de referencia son adultas.
Muchos LoRA de texto a imagen son excelentes estilistas y anatomistas poco fiables. Pueden elegir un objetivo, iluminar una habitación, reproducir una atmósfera fotográfica y luego decidir discretamente que uno o dos detalles anatómicos nunca formaron parte del contrato. Este LoRA fue entrenado para ayudar a corregir precisamente esa debilidad.
El problema cuenta incluso con un respetable precedente mitológico.
El Pixiu(貔貅,píxiū; AFI: [pʰi˧˥ ɕjoʊ̯˥˥]), criatura china que atrae la riqueza, tradicionalmente se considera que no tiene ano: excelente para retener tesoros, menos convincente como anatomía. En Occidente, la Anfisbena suele representarse como una serpiente con una cabeza en cada extremo. Si ambos extremos pertenecen a la gerencia, al parecer nadie quedó a cargo de la plomería.
Y, siguiendo el espíritu de un diálogo de una novela superventas —parafraseado libremente aquí, no presentado como cita textual—:
«¿Por qué tardaste tanto?», preguntó él.
Ella lo miró fijamente. «Sabes que las mujeres no van al baño solo a orinar, ¿verdad?»
Su expresión vacía respondió por él.
«Claro», dijo ella. «Otro aterrador misterio del cuerpo femenino».
La lección práctica es sencilla: vean menos videos cortos que fragmentan la atención y lean más libros. Como mínimo, los libros suelen explicar por qué alguien se ausentó más de treinta segundos.
Porque la v1 fracasó. No en el sentido cinematográfico: ninguna GPU se incendió y ningún ingeniero atravesó el laboratorio cargando un SSD humeante. El entrenamiento terminó, produjo imágenes y luego demostró que completar una ejecución no equivale a aprender la lección prevista. La v2 es lo que ocurre cuando la validación sustituye al optimismo.
Este es un LoRA de asistencia anatómica, no un modelo autónomo completo de personaje, identidad, estilo o composición. Suele ser más útil cuando se combina con otro LoRA NSFW que ya proporciona la persona, el lenguaje visual, la escena o el carácter fotográfico.
| Elemento | Valor |
|---|---|
| Modelo base | Qwen Image 2512 |
| Imágenes de entrenamiento | 1.046 |
| GPU | NVIDIA RTX PRO 6000 Blackwell / 96 GB |
| Rank | 32 |
| Tamaño del lote | 8 |
| Pasos de entrenamiento | 7.600 |
| Activador | Ninguno — solo lenguaje natural |
0.4-0.8 y luego ajústelo según el LoRA principal y el promptNo se recomienda utilizar este LoRA como único adaptador activo. Por sí solo puede influir en la anatomía explícita, pero no aporta la identidad general, el estilo, el entorno ni la distribución fotográfica que se espera de un LoRA principal.
Cada fila compara la misma prueba sin y con el LoRA de corrección anatómica.
| Sin el LoRA de corrección anatómica | Con la v2 sin activador |
|---|---|
![]() | ![]() |
| Sin el LoRA de corrección anatómica | Con la v2 sin activador |
|---|---|
![]() | ![]() |
| Sin el LoRA de corrección anatómica | Con la v2 sin activador |
|---|---|
![]() | ![]() |
| Sin el LoRA de corrección anatómica | Con la v2 sin activador |
|---|---|
![]() | ![]() |
No pase todo el día ampliando generaciones hasta que cada píxel parezca una urgencia médica. Reduzca el peso del LoRA, compare con una referencia limpia, salga a caminar y lea un libro. Los libros son más lentos que los videos cortos, pero ofrecen mucho más contexto y, de vez en cuando, recuerdan que las mujeres poseen sistemas digestivos completos.
Los archivos descargables reference.py y reference_low_vram.py cargan Qwen-Image-2512 en BF16, fusionan el adaptador Lightning de la comunidad y aplican este LoRA de corrección anatómica sin activador. Se recomienda una GPU CUDA con mucha memoria para la versión estándar.
pip install -U diffusers transformers accelerate peft safetensors
<details>
<summary><strong>▶ Mostrar el código Python estándar</strong></summary>
"""Qwen Image 2512 + triggerless Female Anatomy Fix LoRA v2."""
import math
import torch
from diffusers import DiffusionPipeline, FlowMatchEulerDiscreteScheduler
BASE_MODEL_ID = "Qwen/Qwen-Image-2512"
LIGHTNING_MODEL_ID = "lightx2v/Qwen-Image-2512-Lightning"
LIGHTNING_WEIGHT_NAME = (
"Qwen-Image-2512-Lightning-4steps-V1.0-bf16.safetensors"
)
LORA_MODEL_ID = (
"perpetual3x/Qwen-Image-Female-Anatomy-Fix-NSFW-LoRA-Triggerless-v2"
)
LORA_WEIGHT_NAME = "anusv2.safetensors"
DEVICE = "cuda"
DTYPE = torch.bfloat16
LORA_SCALE = 0.4
scheduler_config = {
"base_image_seq_len": 256,
"base_shift": math.log(3),
"invert_sigmas": False,
"max_image_seq_len": 8192,
"max_shift": math.log(3),
"num_train_timesteps": 1000,
"shift": 1.0,
"shift_terminal": None,
"stochastic_sampling": False,
"time_shift_type": "exponential",
"use_beta_sigmas": False,
"use_dynamic_shifting": True,
"use_exponential_sigmas": False,
"use_karras_sigmas": False,
}
scheduler = FlowMatchEulerDiscreteScheduler.from_config(scheduler_config)
pipe = DiffusionPipeline.from_pretrained(
BASE_MODEL_ID,
scheduler=scheduler,
torch_dtype=DTYPE,
).to(DEVICE)
pipe.load_lora_weights(
LIGHTNING_MODEL_ID,
weight_name=LIGHTNING_WEIGHT_NAME,
adapter_name="lightning",
)
pipe.fuse_lora(adapter_names=["lightning"], lora_scale=1.0)
pipe.unload_lora_weights()
pipe.load_lora_weights(
LORA_MODEL_ID,
weight_name=LORA_WEIGHT_NAME,
adapter_name="anatomy_fix_v2",
)
pipe.set_adapters(["anatomy_fix_v2"], adapter_weights=[LORA_SCALE])
# Natural language only: no trigger word is required.
prompt = (
"A realistic photograph of an adult woman, anatomically coherent external "
"female anatomy, natural pelvic structure, realistic skin texture, "
"physically plausible pose and lighting"
)
negative_prompt = (
"child, minor, underage, youthful, low quality, blurry, distorted anatomy, "
"extra limbs, duplicated body parts, fused anatomy, watermark, logo, text"
)
generator = torch.Generator(device=DEVICE).manual_seed(42)
image = pipe(
prompt=prompt,
negative_prompt=negative_prompt,
width=928,
height=1328,
num_inference_steps=8,
true_cfg_scale=1.0,
generator=generator,
).images[0]
image.save("female_anatomy_fix_v2.png")
</details>
<details>
<summary><strong>▶ Mostrar el código Python para poca VRAM</strong></summary>
"""Low-VRAM Qwen Image 2512 + triggerless Female Anatomy Fix LoRA v2."""
import gc
import math
import torch
from diffusers import DiffusionPipeline, FlowMatchEulerDiscreteScheduler
BASE_MODEL_ID = "Qwen/Qwen-Image-2512"
LIGHTNING_MODEL_ID = "lightx2v/Qwen-Image-2512-Lightning"
LIGHTNING_WEIGHT_NAME = (
"Qwen-Image-2512-Lightning-4steps-V1.0-bf16.safetensors"
)
LORA_MODEL_ID = (
"perpetual3x/Qwen-Image-Female-Anatomy-Fix-NSFW-LoRA-Triggerless-v2"
)
LORA_WEIGHT_NAME = "anusv2.safetensors"
DTYPE = torch.bfloat16
LORA_SCALE = 0.4
scheduler_config = {
"base_image_seq_len": 256,
"base_shift": math.log(3),
"invert_sigmas": False,
"max_image_seq_len": 8192,
"max_shift": math.log(3),
"num_train_timesteps": 1000,
"shift": 1.0,
"shift_terminal": None,
"stochastic_sampling": False,
"time_shift_type": "exponential",
"use_beta_sigmas": False,
"use_dynamic_shifting": True,
"use_exponential_sigmas": False,
"use_karras_sigmas": False,
}
gc.collect()
if torch.cuda.is_available():
torch.cuda.empty_cache()
scheduler = FlowMatchEulerDiscreteScheduler.from_config(scheduler_config)
pipe = DiffusionPipeline.from_pretrained(
BASE_MODEL_ID,
scheduler=scheduler,
torch_dtype=DTYPE,
low_cpu_mem_usage=True,
)
pipe.load_lora_weights(
LIGHTNING_MODEL_ID,
weight_name=LIGHTNING_WEIGHT_NAME,
adapter_name="lightning",
)
pipe.fuse_lora(adapter_names=["lightning"], lora_scale=1.0)
pipe.unload_lora_weights()
pipe.load_lora_weights(
LORA_MODEL_ID,
weight_name=LORA_WEIGHT_NAME,
adapter_name="anatomy_fix_v2",
)
pipe.set_adapters(["anatomy_fix_v2"], adapter_weights=[LORA_SCALE])
pipe.enable_sequential_cpu_offload()
pipe.vae.enable_tiling()
pipe.vae.enable_slicing()
# Natural language only: no trigger word is required.
prompt = (
"A realistic photograph of an adult woman, anatomically coherent external "
"female anatomy, natural pelvic structure, realistic skin texture, "
"physically plausible pose and lighting"
)
negative_prompt = (
"child, minor, underage, youthful, low quality, blurry, distorted anatomy, "
"extra limbs, duplicated body parts, fused anatomy, watermark, logo, text"
)
generator = torch.Generator(device="cpu").manual_seed(42)
image = pipe(
prompt=prompt,
negative_prompt=negative_prompt,
width=768,
height=1024,
num_inference_steps=8,
true_cfg_scale=1.0,
generator=generator,
).images[0]
image.save("female_anatomy_fix_v2_low_vram.png")
</details>
Este modelo está destinado exclusivamente a trabajos creativos legales, consensuados y con personas adultas. No lo utilice para:
Los usuarios son responsables de garantizar que sus prompts, materiales de origen y contenidos generados cumplan las leyes aplicables y las políticas de las plataformas.
Este LoRA solo puede utilizarse con fines personales y no comerciales. Consulte el archivo LICENSE del repositorio para conocer las condiciones completas.
Para consultas sobre licencias comerciales, póngase en contacto con el autor.
El modelo anunciado aquí ya está publicado: Qwen Image Male Anatomy Realism - NSFW LoRA v1. El texto y las imágenes siguientes se conservan como avance histórico de su desarrollo.
Después de dedicar tanto tiempo a recordarles a los modelos de imagen que las mujeres poseen una anatomía completa, la justicia exige pedir lo mismo para los hombres. El próximo proyecto se centrará en una anatomía masculina adulta coherente: el glande, el pene, el escroto, la inserción púbica, el perineo y el pequeño pero aparentemente controvertido detalle de que dos testículos deberían parecer dos testículos, no una papa ambiciosa con un filtro de textura de piel.
La mayoría de los modelos existentes que he visto parecen ofrecer dos ajustes: «un dildo que de algún modo consiguió un torso» o «un proyecto de ingeniería mitológica rechazado por exceder el presupuesto». El primero olvida que la anatomía tiene una base, tejidos, peso y algún lugar razonable donde conectarse; el segundo les entrega a las mujeres la ficha técnica equivocada y manda a hombres perfectamente normales a una evaluación de desempeño completamente innecesaria con su propia autoestima. El objetivo no es ganar una carrera armamentista anatómica que nadie pidió, sino producir una anatomía masculina adulta creíble.
Estas imágenes son avances de un proyecto independiente todavía en desarrollo, no resultados de este LoRA de corrección de anatomía femenina. Todas las personas representadas son adultas.
<details> <summary><strong>🔞 Haz clic para mostrar los avances explícitos de anatomía masculina adultaLa siguiente sección contiene estudios anatómicos directos de hombres adultos. Está contraída de forma predeterminada para que verla sea una elección deliberada y no un cambio de paisaje inesperado. </strong></summary>



Adult content warning: This repository contains explicit AI-generated imagery and is intended only for adults. Every person described in the examples and reference prompts is an adult.
Many text-to-image LoRAs are excellent stylists and unreliable anatomists. They can choose a lens, light a room, reproduce a photographic mood, and then quietly decide that one or two anatomical details were never part of the contract. This LoRA was trained to help correct that specific weakness.
There is respectable mythological precedent for the problem.
Pixiu(貔貅,píxiū; IPA: [pʰi˧˥ ɕjoʊ̯˥˥]), the Chinese wealth-attracting beast, is traditionally believed to have no anus - excellent for retaining treasure, less convincing as anatomy. The Western Amphisbaena is often depicted as a serpent with a head at each end. If both ends are management, apparently nobody was assigned to plumbing.
And, in the spirit of a bestselling-novel exchange - loosely paraphrased here rather than presented as a direct quotation:
"What took you so long?" he asked.
She stared at him. "You do realize women don't go to the bathroom just to piss, don't you?"
His blank expression answered for him.
"Right," she said. "Another terrifying mystery of the female body."
The practical lesson is simple: watch fewer attention-fragmenting short videos and read more books. At minimum, books tend to explain why someone was gone for longer than thirty seconds.
Because v1 failed. Not in the cinematic sense - no GPU caught fire and no engineer ran through a laboratory carrying a smoking SSD. It completed training, produced images, and then demonstrated that finishing a run is not the same thing as learning the intended lesson. V2 is what happens when optimism is replaced by validation.
This is an anatomy-assist LoRA, not a complete standalone character, identity, style, or composition model. It is usually most useful when paired with another NSFW LoRA that already supplies the person, visual language, scene, or photographic character.
| Item | Value |
|---|---|
| Base model | Qwen Image 2512 |
| Training images | 1,046 |
| GPU | NVIDIA RTX PRO 6000 Blackwell / 96 GB |
| Rank | 32 |
| Batch size | 8 |
| Training steps | 7,600 |
| Trigger | None - natural language only |
0.4-0.8, then adjust for the primary LoRA and promptThis LoRA is not recommended as the only active adapter. Used alone, it may influence explicit anatomy but does not provide the broader identity, styling, environment, or photographic distribution that a primary LoRA is expected to supply.
Each row compares the same test setup without and with the anatomy-fix LoRA.
| Without anatomy-fix LoRA | With Triggerless v2 |
|---|---|
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| Without anatomy-fix LoRA | With Triggerless v2 |
|---|---|
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| Without anatomy-fix LoRA | With Triggerless v2 |
|---|---|
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| Without anatomy-fix LoRA | With Triggerless v2 |
|---|---|
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Do not spend the whole day zooming into generations until every pixel begins to look like a medical emergency. Reduce the LoRA weight, compare against a clean baseline, take a walk, and read a book. Books are slower than short videos, but they are considerably better at context - and occasionally at remembering that women possess complete digestive systems.
The downloadable reference.py and reference_low_vram.py load Qwen-Image-2512 in BF16, fuse the community Lightning adapter, and apply this triggerless anatomy-fix LoRA. A high-memory CUDA GPU is recommended for the standard version.
pip install -U diffusers transformers accelerate peft safetensors
<details>
<summary><strong>▶ Show Standard Python Reference</strong></summary>
"""Qwen Image 2512 + triggerless Female Anatomy Fix LoRA v2."""
import math
import torch
from diffusers import DiffusionPipeline, FlowMatchEulerDiscreteScheduler
BASE_MODEL_ID = "Qwen/Qwen-Image-2512"
LIGHTNING_MODEL_ID = "lightx2v/Qwen-Image-2512-Lightning"
LIGHTNING_WEIGHT_NAME = (
"Qwen-Image-2512-Lightning-4steps-V1.0-bf16.safetensors"
)
LORA_MODEL_ID = (
"perpetual3x/Qwen-Image-Female-Anatomy-Fix-NSFW-LoRA-Triggerless-v2"
)
LORA_WEIGHT_NAME = "anusv2.safetensors"
DEVICE = "cuda"
DTYPE = torch.bfloat16
LORA_SCALE = 0.4
scheduler_config = {
"base_image_seq_len": 256,
"base_shift": math.log(3),
"invert_sigmas": False,
"max_image_seq_len": 8192,
"max_shift": math.log(3),
"num_train_timesteps": 1000,
"shift": 1.0,
"shift_terminal": None,
"stochastic_sampling": False,
"time_shift_type": "exponential",
"use_beta_sigmas": False,
"use_dynamic_shifting": True,
"use_exponential_sigmas": False,
"use_karras_sigmas": False,
}
scheduler = FlowMatchEulerDiscreteScheduler.from_config(scheduler_config)
pipe = DiffusionPipeline.from_pretrained(
BASE_MODEL_ID,
scheduler=scheduler,
torch_dtype=DTYPE,
).to(DEVICE)
pipe.load_lora_weights(
LIGHTNING_MODEL_ID,
weight_name=LIGHTNING_WEIGHT_NAME,
adapter_name="lightning",
)
pipe.fuse_lora(adapter_names=["lightning"], lora_scale=1.0)
pipe.unload_lora_weights()
pipe.load_lora_weights(
LORA_MODEL_ID,
weight_name=LORA_WEIGHT_NAME,
adapter_name="anatomy_fix_v2",
)
pipe.set_adapters(["anatomy_fix_v2"], adapter_weights=[LORA_SCALE])
# Natural language only: no trigger word is required.
prompt = (
"A realistic photograph of an adult woman, anatomically coherent external "
"female anatomy, natural pelvic structure, realistic skin texture, "
"physically plausible pose and lighting"
)
negative_prompt = (
"child, minor, underage, youthful, low quality, blurry, distorted anatomy, "
"extra limbs, duplicated body parts, fused anatomy, watermark, logo, text"
)
generator = torch.Generator(device=DEVICE).manual_seed(42)
image = pipe(
prompt=prompt,
negative_prompt=negative_prompt,
width=928,
height=1328,
num_inference_steps=8,
true_cfg_scale=1.0,
generator=generator,
).images[0]
image.save("female_anatomy_fix_v2.png")
</details>
<details>
<summary><strong>▶ Show Low-VRAM Python Reference</strong></summary>
"""Low-VRAM Qwen Image 2512 + triggerless Female Anatomy Fix LoRA v2."""
import gc
import math
import torch
from diffusers import DiffusionPipeline, FlowMatchEulerDiscreteScheduler
BASE_MODEL_ID = "Qwen/Qwen-Image-2512"
LIGHTNING_MODEL_ID = "lightx2v/Qwen-Image-2512-Lightning"
LIGHTNING_WEIGHT_NAME = (
"Qwen-Image-2512-Lightning-4steps-V1.0-bf16.safetensors"
)
LORA_MODEL_ID = (
"perpetual3x/Qwen-Image-Female-Anatomy-Fix-NSFW-LoRA-Triggerless-v2"
)
LORA_WEIGHT_NAME = "anusv2.safetensors"
DTYPE = torch.bfloat16
LORA_SCALE = 0.4
scheduler_config = {
"base_image_seq_len": 256,
"base_shift": math.log(3),
"invert_sigmas": False,
"max_image_seq_len": 8192,
"max_shift": math.log(3),
"num_train_timesteps": 1000,
"shift": 1.0,
"shift_terminal": None,
"stochastic_sampling": False,
"time_shift_type": "exponential",
"use_beta_sigmas": False,
"use_dynamic_shifting": True,
"use_exponential_sigmas": False,
"use_karras_sigmas": False,
}
gc.collect()
if torch.cuda.is_available():
torch.cuda.empty_cache()
scheduler = FlowMatchEulerDiscreteScheduler.from_config(scheduler_config)
pipe = DiffusionPipeline.from_pretrained(
BASE_MODEL_ID,
scheduler=scheduler,
torch_dtype=DTYPE,
low_cpu_mem_usage=True,
)
pipe.load_lora_weights(
LIGHTNING_MODEL_ID,
weight_name=LIGHTNING_WEIGHT_NAME,
adapter_name="lightning",
)
pipe.fuse_lora(adapter_names=["lightning"], lora_scale=1.0)
pipe.unload_lora_weights()
pipe.load_lora_weights(
LORA_MODEL_ID,
weight_name=LORA_WEIGHT_NAME,
adapter_name="anatomy_fix_v2",
)
pipe.set_adapters(["anatomy_fix_v2"], adapter_weights=[LORA_SCALE])
pipe.enable_sequential_cpu_offload()
pipe.vae.enable_tiling()
pipe.vae.enable_slicing()
# Natural language only: no trigger word is required.
prompt = (
"A realistic photograph of an adult woman, anatomically coherent external "
"female anatomy, natural pelvic structure, realistic skin texture, "
"physically plausible pose and lighting"
)
negative_prompt = (
"child, minor, underage, youthful, low quality, blurry, distorted anatomy, "
"extra limbs, duplicated body parts, fused anatomy, watermark, logo, text"
)
generator = torch.Generator(device="cpu").manual_seed(42)
image = pipe(
prompt=prompt,
negative_prompt=negative_prompt,
width=768,
height=1024,
num_inference_steps=8,
true_cfg_scale=1.0,
generator=generator,
).images[0]
image.save("female_anatomy_fix_v2_low_vram.png")
</details>
This model is intended exclusively for lawful, consensual, adult creative work. Do not use it to:
Users are responsible for ensuring that their prompts, source material, and generated content comply with applicable laws and platform policies.
This LoRA may be used for personal and non-commercial purposes only. See the repository LICENSE file for the complete terms.
For commercial licensing inquiries, please contact the author.
The model announced here has now been released: Qwen Image Male Anatomy Realism - NSFW LoRA v1. The text and images below are preserved as a historical preview of its development.
After spending this much time reminding image models that women possess complete anatomy, fairness requires asking the same of men. The next project will focus on coherent adult male anatomy: the glans, shaft, scrotum, pubic attachment, perineum, and the small but apparently controversial detail that two testicles should look like two testicles—not one ambitious potato wearing a skin-texture filter.
Most existing models I have seen seem to offer two settings: “a dildo that has somehow acquired a torso” or “a mythological engineering project rejected for budget overruns.” The first forgets that anatomy has roots, tissue, weight, and somewhere sensible to connect; the second gives women the wrong specification sheet and sends perfectly normal men into an entirely unnecessary performance review with their own self-esteem. The goal here is not to win an anatomical arms race nobody asked for, but to produce believable adult male anatomy.
These are early previews from a separate work in progress, not outputs from this Female Anatomy Fix LoRA. All depicted subjects are adults.
<details> <summary><strong>🔞 Click to reveal explicit adult male anatomy previewsThe following section contains direct adult male anatomical studies. It is collapsed by default so that viewing it is a deliberate choice rather than an unexpected change of scenery. </strong></summary>

