Downloads · 30 days
1.8K
8% of all-time downloads
Linaqruf/hitokomoru-diffusion
hitokomoru-diffusion is a text-to-image model from Linaqruf. Use it when you need an image from a text prompt. It is set up for diffusers. The card lists the license as creativeml-openrail-m.
Welcome to Hitokomoru Diffusion - a latent diffusion model that has been trained on Japanese Artist artwork, ヒトこもる/Hitokomoru. The current model has been fine-tuned with a learning rate of 2.0e-6 for 20000 training st…
Downloads · 30 days
1.8K
8% of all-time downloads
All-time downloads
23.2K
Public
Repo size
83.5 GB
Likes
77
Public
Click a slice to open those files.
.ckpt56.5 GB · 91%
From the Hugging Face model README
Welcome to Hitokomoru Diffusion - a latent diffusion model that has been trained on Japanese Artist artwork, ヒトこもる/Hitokomoru. The current model has been fine-tuned with a learning rate of 2.0e-6 for 20000 training steps/80 Epochs on 255 images collected from Danbooru. The model is trained using NovelAI Aspect Ratio Bucketing Tool so that it can be trained at non-square resolutions. Like other anime-style Stable Diffusion models, it also supports Danbooru tags to generate images.
e.g. 1girl, white hair, golden eyes, beautiful eyes, detail, flower meadow, cumulonimbus clouds, lighting, detailed sky, garden
There is 4 variations of this model available so far:
hitokomoru-5000.ckpt for the checkpoint trained on 5,000 steps.hitokomoru-10000.ckpt for the checkpoint trained on 10,000 steps.hitokomoru-15000.ckpt for the checkpoint trained on 15,000 steps.hitokomoru-20000.ckpt for the checkpoint trained on 20,000 steps.You can find datasets used to train this model and the last-state folder for resume training here
This model can be used just like any other Stable Diffusion model. For more information, please have a look at the Stable Diffusion.
You can also export the model to ONNX, MPS and/or FLAX/JAX.
from diffusers import StableDiffusionPipeline
import torch
model_id = "Linaqruf/hitokomoru-diffusion"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to("cuda")
prompt = "hatsune_miku"
image = pipe(prompt).images[0]
image.save("./hatsune_miku.png")
Below are some examples of images generated using this model:
Anime Girl:

Anime Boy:

Anime Girl:

Anime Boy:

Anime Girl:

Anime Boy:

Anime Girl:

Anime Boy:

Anime Girl:
(masterpiece:1.05),illustration,beautiful detailed,colourful,finely detailed,dramatic light,intricate details,1 girl, 1990, 1980, hatsune miku
Negative prompt:
nsfw, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry,missing fingers,bad hands,missing arms, long neck, Humpbacked,shadow,long body, Abnormal fingers,
Steps: 32, Sampler: Euler, CFG scale: 10, Seed: 2319346364, Size: 512x768, Model hash: 2700c435, Batch size: 2, Batch pos: 0, Clip skip: 2
Anime Boy:
Authentic and detailed face(man:1.2763)(boymasterpiece:1.1025), (best quality:1.1025), (ultra-detailed:1.1025), (illustration:1.1025), (tousled hair:1.1025), (frill:0.907) , white cutter shirt, (one boy:1.05), (solo:1.05) chest, detailed wet clothes, empty stare, pants, (flowers:1.05), beautifully detailed sky, beautifully detailed water, leaves, detailed and beautiful sea
Negative prompt:
(big breasts:1.2763)(breast:1.1025)}(woman:1.2155)} little girl,(3d:1.1576)(girl:1.629), nsfw, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry,missing fingers,bad hands,missing arms, long neck, Humpbacked
Steps: 40, Sampler: DPM++ 2M Karras, CFG scale: 7, Seed: 1870332858, Size: 512x768, Model hash: 2700c435, Batch size: 2, Batch pos: 0, Clip skip: 2
This model is open access and available to all, with a CreativeML OpenRAIL-M license further specifying rights and usage. The CreativeML OpenRAIL License specifies: