Instructions to use suzushi/miso_diffusion_xl_1.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use suzushi/miso_diffusion_xl_1.2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("suzushi/miso_diffusion_xl_1.2", torch_dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Anime SDXL Model
A Stable Diffusion XL model fine-tuned for generating high-quality anime-style images.
Version History
| Version | Base Training | Aesthetic Training | Total Epochs |
|---|---|---|---|
| 1.0 | 160K images | 10K images | 5 |
| 1.1 | 200K images | 12K images | 5 |
| 1.2 | - | 23K images | 9 |
Training Methodology
The model underwent a multi-stage training process:
Base Pre-training
- Initial training on a diverse dataset of anime-style images
- Focus on learning fundamental anime art styles and characteristics
Aesthetic Fine-tuning
- Secondary training phase focusing on artistic quality and consistency
- Curated dataset of high-quality anime artwork
- Progressive improvements across versions
- Downloads last month
- 6
Model tree for suzushi/miso_diffusion_xl_1.2
Base model
stabilityai/stable-diffusion-xl-base-1.0 Finetuned
suzushi/miso-diffusion-xl-1.0