Instructions to use ProGamerGov/Min-Illust-Background-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ProGamerGov/Min-Illust-Background-Diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ProGamerGov/Min-Illust-Background-Diffusion", 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
| license: creativeml-openrail-m | |
| tags: | |
| - stable-diffusion | |
| - text-to-image | |
| datasets: | |
| - ProGamerGov/StableDiffusion-v1-5-Regularization-Images | |
| **Min-Illust-Background-Diffusion** | |
| This fine-tuned Stable Diffusion v1.5 model was trained for 2250 iterations with a batch size of 4, on a selection of artistic works by Sin Jong Hun. Training was performed using [ShivamShrirao/diffusers](https://github.com/ShivamShrirao/diffusers) with full precision, prior-preservation loss, the train-text-encoder feature, and the new [1.5 MSE VAE from Stability AI](https://huggingface.co/stabilityai/sd-vae-ft-mse). A total of 4120 regularization / class images were used from [here](https://huggingface.co/datasets/ProGamerGov/StableDiffusion-v1-5-Regularization-Images). Regularization images were generated using the prompt "artwork style", 50 DDIM steps, and a CFG of 7. | |
| Use the tokens **sjh style** in your prompts for the effect. Note that the effect also appears to occur at a much weaker strength on prompts that steer the output towards specific artistic styles. | |
| This model will likely not perform well on generating portraits and related tasks, as the training data was primarily composed of landscapes. | |
| <div align="center"> | |
| <img src="https://huggingface.co/ProGamerGov/Min-Illust-Background-Diffusion/resolve/main/v1_size_512x768_t3x4.png"> | |
| </div> | |
| * [Full Image](https://huggingface.co/ProGamerGov/Min-Illust-Background-Diffusion/resolve/main/v1_size_512x768_t3x4.png) | |
| <div align="center"> | |
| <img src="https://huggingface.co/ProGamerGov/Min-Illust-Background-Diffusion/resolve/main/v1_size_512x512_t4x10.png"> | |
| </div> | |
| * [Full Image](https://huggingface.co/ProGamerGov/Min-Illust-Background-Diffusion/resolve/main/v1_size_512x512_t4x10.png) | |
| <div align="center"> | |
| <img src="https://huggingface.co/ProGamerGov/Min-Illust-Background-Diffusion/resolve/main/v1_512x512_t4x5.png"> | |
| </div> | |
| * [Full Image](https://huggingface.co/ProGamerGov/Min-Illust-Background-Diffusion/resolve/main/v1_512x512_t4x5.png) | |
| Example images were generated with the v1 2250 iteration model using 50 steps of DPM++ 2M Karras with a format of: | |
| ``` | |
| <prompt>, sjh style | |
| ``` | |