Instructions to use google/ddpm-cat-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use google/ddpm-cat-256 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("google/ddpm-cat-256", 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
Commit ·
34e20c9
1
Parent(s): 651128a
Update README.md
Browse files
README.md
CHANGED
|
@@ -46,11 +46,11 @@ image = ddpm()["sample"]
|
|
| 46 |
image[0].save("ddpm_generated_image.png")
|
| 47 |
```
|
| 48 |
|
| 49 |
-
For more in-detail information, please have a look at the [official inference example](
|
| 50 |
|
| 51 |
## Training
|
| 52 |
|
| 53 |
-
If you want to train your own model, please have a look at the [official training example](
|
| 54 |
|
| 55 |
## Samples
|
| 56 |
1. 
|
|
|
|
| 46 |
image[0].save("ddpm_generated_image.png")
|
| 47 |
```
|
| 48 |
|
| 49 |
+
For more in-detail information, please have a look at the [official inference example](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/diffusers_intro.ipynb)
|
| 50 |
|
| 51 |
## Training
|
| 52 |
|
| 53 |
+
If you want to train your own model, please have a look at the [official training example](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/training_example.ipynb)
|
| 54 |
|
| 55 |
## Samples
|
| 56 |
1. 
|