Instructions to use Hishambarakat/checkpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Hishambarakat/checkpoint with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Hishambarakat/checkpoint", 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
Ctrl+K
- 4.24 GB xet
- 2.13 GB xet
- 2.13 GB xet
- 2.13 GB xet
- 5.67 GB xet
- 3.46 GB xet
- 2.13 GB xet
- 2.4 GB xet
- 2.3 GB xet
- 3.46 GB xet
- 2.13 GB xet
- 2.13 GB xet
- 2.13 GB xet
- 2.13 GB xet
- 4.41 GB xet
- 2.4 GB xet
- 4.51 GB xet
- 2.13 GB xet
- 2.4 GB xet
- 2.13 GB xet
- 2.13 GB xet
- 2.13 GB xet
- 2.4 GB xet
- 2.4 GB xet
- 2.4 GB xet
- 4.27 GB xet
- 5.23 GB xet
- 2.13 GB xet
- 2.38 GB xet
- 2.13 GB xet
- 2.13 GB xet
- 2.3 GB xet
- 2.4 GB xet
- 2.13 GB xet
- 7.7 GB xet
- 4.53 GB xet
- 4.27 GB xet
- 4.27 GB xet
- 2.13 GB xet
- 4.27 GB xet
- 4.24 GB xet
- 2.13 GB xet
- 2.13 GB xet
- 2.13 GB xet
- 4.27 GB xet
- 2.3 GB xet
- 2.13 GB xet
- 2.13 GB xet
- 2.13 GB xet
- 2.3 GB xet