Instructions to use Lynnxy0/ddpm-floorplans_tutorial-128_bw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Lynnxy0/ddpm-floorplans_tutorial-128_bw with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Lynnxy0/ddpm-floorplans_tutorial-128_bw", 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 History
-
Epoch 99
c904e67 -
Epoch 89
7cc4977 -
Epoch 79
d305bd7 -
Epoch 69
72a047b -
Epoch 59
d35e604 -
Epoch 49
d263303 -
Epoch 39
65dce0a -
Epoch 29
1a992ce -
Epoch 19
06f2916 -
Epoch 9
632c0b6 -
Epoch 39
5c6e4de -
Epoch 29
0d8023b -
Epoch 19
8833b61 -
Epoch 9
1c13ec6
-
Epoch 29
e07cd2a -
Epoch 19
0072dca -
Epoch 9
7a84b6e
-
Epoch 99
cd37dd1 -
Epoch 89
1608eeb -
Epoch 79
acb01eb -
Epoch 69
560f176 -
Epoch 59
2724edd -
Epoch 49
d5b5602 -
Epoch 39
5fd1467 -
Epoch 29
28a1669 -
Epoch 19
68aa8a5 -
Epoch 9
c19d8a1