Name: Slime Girl Concept
Rating: 5 (1880 reviews)
Author: motimalu

adult toys

anal

blowjob

breast out

breasts out

child on child

convenient censoring

corpses

covered nipples

diapers

dildo riding

disturbing

downblouse

emaciated bodies

exposed female nipple

extremist

female nudity

female swimwear

female swimwear or underwear

female underwear

futanari

genitals

gigantic breasts

graphic female nudity

graphic male nudity

graphic violence or gore

hair over breasts

hanging

hate speech

hate symbols

hentai

huge breasts

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illustrated explicit nudity

incest

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male nudity

male swimwear or underwear

male underwear

nazi party

no panties

nsfw

nude

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one breast out

oral

oral invitation

partial nudity

peeing

pg-13

physical violence

porn

revealing clothes

scat

self injury

sexual activity

sexual intent

sexual situations

sexy

sitting on face

strapless leotard

suggestive

thick thighs

undressed

urine

vore

weapon violence

white supremacy

wide hips

bukkake

fellatio

bikini

cumshot

implied fellatio

eat_cum

cumdrip

cum in pussy

cum on face

after fellatio

cum on hair

cum on body

cum on tongue

cum on hands

cum in mouth

presenting ass

<h1 id="slime-girl-concept-tlt3eblwd">Slime Girl Concept</h1>Just some friendly slime girls of all different types and colors. ꒷꒦ℹ️ LoRA work best when applied to the base models on which they are trained. Please read the About This Version on the appropriate base models and workflow/training information.<h3 id="license-92mggm3y8">License</h3><a target="_blank" rel="ugc" href="https://freedevproject.org/faipl-1.0-sd/">Fair AI Public License 1.0-SD</a>

Trained on <a target="_blank" rel="ugc" href="https://huggingface.co/Qwen/Qwen-Image">Qwen Image</a>Using the default <a target="_blank" rel="ugc" href="https://github.com/tdrussell/diffusion-pipe/blob/4a61bcfd82eb8d54a807ac7a15f548fab73ae5e1/examples/qwen_image_24gb_vram.toml">diffusion-pipe qwen config</a>Dataset resolution of 640Previews generated with the lightx2v Lighting 4step LoRA:<a target="_blank" rel="ugc" href="https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Lightning-4steps-V1.0.safetensors">https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Lightning-4steps-V1.0.safetensors</a>

v1.0 [qwen]

Trained on <a target="_blank" rel="ugc" href="https://civitai.com/models/795765/illustrious-xl">Illustrious XL 0.1</a>With an updated dataset:<ul><li>919 images</li><li>manually rated <code>masterpiece, best quality, very aesthetic</code> tags</li><li>tagged <code>nsfw</code> <code>explicit</code> with imgutils anime_rating</li><li>included a small <code>water dress</code> concept dataset</li></ul>

v1.0 [Illustrious]

[WAN 14B] LoRA<ul><li>Trained with <a target="_blank" rel="ugc" href="https://github.com/tdrussell/diffusion-pipe">diffusion-pipe</a> on <a target="_blank" rel="ugc" href="https://huggingface.co/Wan-AI/Wan2.1-T2V-14B">Wan2.1-T2V-14B</a></li><li>Seems usable for both text-to-video and image-to-video workflows with Wan</li><li>Text to Video previews generated with <a target="_blank" rel="ugc" href="https://comfyanonymous.github.io/ComfyUI_examples/wan/#text-to-video">ComfyUI_examples/wan/#text-to-video</a><ul><li>Loading the LoRA with LoraLoaderModelOnly node and using the fp8 14B <a target="_blank" rel="ugc" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/diffusion_models/wan2.1_t2v_14B_fp8_scaled.safetensors">wan2.1_t2v_14B_fp8_scaled.safetensors</a></li></ul></li><li>Image to Video previews generated with <a target="_blank" rel="ugc" href="https://comfyanonymous.github.io/ComfyUI_examples/wan/#image-to-video">ComfyUI_examples/wan/#image-to-video</a><ul><li>Using image generations from the IL/Noobai versions of this model card</li></ul></li></ul>

v1.0 [wan-t2v-14b]

Brings slimes to life in Hunyuan T2V generations!Trained with <a target="_blank" rel="ugc" href="https://github.com/tdrussell/diffusion-pipe">https://github.com/tdrussell/diffusion-pipe</a>Training data is small combination of:<ul><li>Images used from other versions this model card</li><li>Images extracted as keyframes from several videos</li><li>Short video clips ~40 frames each</li></ul>Training configs:dataset.toml<pre><code># Aspect ratio bucketing settings
enable_ar_bucket = true
min_ar = 0.5
max_ar = 2.0
num_ar_buckets = 7

[[directory]] # IMAGES
# Path to the directory containing images and their corresponding caption files.
path = '/mnt/d/huanvideo/training_data/images'
num_repeats = 5
resolutions = [1024]
frame_buckets = [1] # Use 1 frame for images.


[[directory]] # VIDEOS
# Path to the directory containing videos and their corresponding caption files.
path = '/mnt/d/huanvideo/training_data/videos'
num_repeats = 5
resolutions = [256] # Set video resolution to 256 (e.g., 244p).
frame_buckets = [33, 49, 81] # Define frame buckets for videos.</code></pre>config.toml<pre><code># Dataset config file.
output_dir = '/mnt/d/huanvideo/training_output'
dataset = 'dataset.toml'

# Training settings
epochs = 50
micro_batch_size_per_gpu = 1
pipeline_stages = 1
gradient_accumulation_steps = 4
gradient_clipping = 1.0
warmup_steps = 100

# eval settings
eval_every_n_epochs = 5
eval_before_first_step = true
eval_micro_batch_size_per_gpu = 1
eval_gradient_accumulation_steps = 1

# misc settings
save_every_n_epochs = 15
checkpoint_every_n_minutes = 30
activation_checkpointing = true
partition_method = 'parameters'
save_dtype = 'bfloat16'
caching_batch_size = 1
steps_per_print = 1
video_clip_mode = 'single_middle'

[model]
type = 'hunyuan-video'

transformer_path = '/mnt/d/huanvideo/models/diffusion_models/hunyuan_video_720_cfgdistill_fp8_e4m3fn.safetensors'
vae_path = '/mnt/d/huanvideo/models/vae/hunyuan_video_vae_bf16.safetensors'
llm_path = '/mnt/d/huanvideo/models/llm'
clip_path = '/mnt/d/huanvideo/models/clip'

dtype = 'bfloat16'
transformer_dtype = 'float8'
timestep_sample_method = 'logit_normal'

[adapter]
type = 'lora'
rank = 32
dtype = 'bfloat16'

[optimizer]
type = 'adamw_optimi'
lr = 5e-5
betas = [0.9, 0.99]
weight_decay = 0.02
eps = 1e-8</code></pre>

v1.0 [hunyuan]

v1.0 [Pony]

<pre><code>「・・・おや！？ スライムのようすが・・・！」</code></pre>Slime girls are evolving!Experimental version trained on AutismMix with an expanded dataset including generated images.Faces will tend not to hold the slime skin colors, but I think they look quite nice, and not a bad trade off for some of the other improvements to style, quality, and the <code>translucent skin</code> concept.

v2.0 [AutismMix]

Slime Girl Concept

motimalu-profile-vid.webp

Type	LoRA
Stats	358 1 10
Reviews	Very Positive (61)
Published	Aug 29, 2025
Base Model	Qwen
Training	Steps: 9,350 Epochs: 50
Usage Tips	Strength: 0.9
Trigger Words	slime girl water dress
Hash	AutoV2 0B2B0B64E9