Instructions to use Andyrasika/avatar_diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Andyrasika/avatar_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("Andyrasika/avatar_diffusion", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Transformers
How to use Andyrasika/avatar_diffusion with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Andyrasika/avatar_diffusion", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Commit ·
429d78c
1
Parent(s): ea17913
Update README.md
Browse files
README.md
CHANGED
|
@@ -17,6 +17,7 @@ This text-to-image stable diffusion model was trained with dreambooth.
|
|
| 17 |
Put in a text prompt and generate your own Avatar style image!
|
| 18 |
|
| 19 |

|
|
|
|
| 20 |
|
| 21 |
```
|
| 22 |
from diffusers import DiffusionPipeline, UniPCMultistepScheduler
|
|
|
|
| 17 |
Put in a text prompt and generate your own Avatar style image!
|
| 18 |
|
| 19 |

|
| 20 |
+
(Image taken from Lambdalabs repo)
|
| 21 |
|
| 22 |
```
|
| 23 |
from diffusers import DiffusionPipeline, UniPCMultistepScheduler
|