Instructions to use ChenHe727/EdgeDiffuse_r4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ChenHe727/EdgeDiffuse_r4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ChenHe727/EdgeDiffuse_r4", 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
- Draw Things
- DiffusionBee
File size: 296 Bytes
22dc910 9ea5cb3 22dc910 b10637a a2c7f41 b10637a 22dc910 | 1 2 3 4 5 6 7 8 9 10 | # To Start
```python
from diffusers import StableDiffusionPipeline
import torch
pipe = StableDiffusionPipeline.from_pretrained("ChenHe727/EdgeDiffuse_r4", torch_dtype=torch.float16)
pipe = pipe.to("cuda")
image = pipe("a photo of a cat", num_inference_steps=4, guidance_scale=0.0).images[0]
``` |