Example Fine-Tuned Model for Unit 2 of the Diffusion Models Class 🧨
This model is a diffusion model for unconditional image generation of Ukiyo-e images ✍ 🎨. The model was train using fine-tuning with the google/ddpm-celebahq-256 pretrain-model and the dataset: https://huggingface.co/datasets/huggan/ukiyoe2photo
- Google Colab notebook for experiment with the model and the sampling process using a Gradio App: https://colab.research.google.com/drive/1F7SH4T9y5fJKxj5lU9HqTzadv836Zj_G?usp=sharing
- Weights&Biases dashboard with training information: https://wandb.ai/alcazar90/fine-tuning-a-diffusion-model?workspace=user-alcazar90
Usage
from diffusers import DDPMPipeline
pipeline = DDPMPipeline.from_pretrained('alkzar90/sd-class-ukiyo-e-256')
image = pipeline().images[0]
image
Guidance
Prompt: A sakura tree
Prompt: An island with sunset at background
- Downloads last month
- 71
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API:
The HF Inference API does not support unconditional-image-generation models for diffusers library.