Instructions to use hdparmar/tradfusion-e5-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hdparmar/tradfusion-e5-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hdparmar/tradfusion-e5-diffusers", 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
File size: 518 Bytes
5bcc922 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ---
license: mit
tags:
- pytorch
- diffusers
- text-to-image
- diffusion-models-class
---
# Example Fine-Tuned Model for Irish Traditional Tunes of the [Diffusion Models Class 🧨](https://github.com/huggingface/diffusion-models-class)
Fine-tuned Stable Diffusion Model for Irish Traditional Tunes (Epoch 5, 33.6k steps)
## Usage
```python
from diffusers import StableDiffusionPipeline
pipeline = StableDiffusionPipeline.from_pretrained('hdparmar/tradfusion-e5-diffusers')
image = pipeline().images[0]
image
```
|