Name: Frieren フリーレン - 葬送のフリーレン
Rating: 5 (38 reviews)
Author: motimalu

sexual situations

physical violence

disturbing

male nudity

extremist

hanging

hate symbols

nazi party

revealing clothes

weapon violence

female swimwear or underwear

male swimwear or underwear

partial nudity

white supremacy

adult toys

graphic male nudity

illustrated explicit nudity

nudity

self injury

graphic violence or gore

graphic female nudity

corpses

wide hips

convenient censoring

peeing

oral invitation

emaciated bodies

exposed female nipple

blowjob

female nudity

sexual activity

sexual intent

undressed

male underwear

female swimwear

genitals

female underwear

thick thighs

breasts out

strapless leotard

vore

bestiality

breast out

one breast out

huge breasts

gigantic breasts

huge butt

covered nipples

hair over breasts

no panties

sitting on face

anal

dildo riding

downblouse

oral

porn

futanari

hentai

nude

lingerie

sexy

nsfw

suggestive

bukkake

cumshot

cumdrip

cum in pussy

cum on face

cum on hair

cum on body

cum on tongue

cum on hands

cum in mouth

cum on pussy

eat_cum

fellatio

implied fellatio

after fellatio

triple fellatio

autofellatio

pov fellatio

fucked silly

presenting ass

presenting pussy

spreading legs

spread legs

swimwear

<h1 id="frieren-p49k95bjf">Frieren フリーレン - 葬送のフリーレン</h1>ℹ️ Check the versions for the respective base modelsThis LoRA is intended to generate images of the character Frieren in a high quality aesthetic illustration style.For other characters, see: <a target="_blank" rel="ugc" href="https://civitai.com/collections/847637">Sousou no Frieren Collection</a><hr /><h3 id="license-4m4a7oigh">License</h3><a target="_blank" rel="ugc" href="https://freedevproject.org/faipl-1.0-sd/">Fair AI Public License 1.0-SD</a>

Trained with <a target="_blank" rel="ugc" href="https://github.com/tdrussell/diffusion-pipe">https://github.com/tdrussell/diffusion-pipe</a>Training data is a 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]

Expanded dataset of 567 images, used an updated tagging approach

v2.0 [Pony]

<ul><li>Experimental version, first try of the Civitai LoRA trainer for Flux</li><li>Future Flux training planned to be done locally with kohya_ss</li><li>Unmodified v2.0 dataset trained on Flux (Danbooru style captions)</li><li>Previews for this version are made with ComfyUI, couldn't get the metadata to save for showing in Civitai<ul><li>Tried the on-site generator for one post with a sample prompt <a target="_blank" rel="ugc" href="https://civitai.com/images/24588380">here</a></li><li>Will use Forge for previews soon (when development for Flux settles)</li></ul></li></ul>

Type	LoRA
Stats	1,404 1,350
Reviews	Very Positive (138)
Published	Aug 16, 2024
Base Model	Flux.1 D
Training	Epochs: 5
Usage Tips	Clip Skip: 1 Strength: 1
Trigger Words	nereirfpnxl, frieren, elf, pointy ears, green eyes, white hair, twintails
Hash	AutoV2 5E0704EDA4