Instructions to use ahilkhanjnv/task2-stable-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ahilkhanjnv/task2-stable-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("ahilkhanjnv/task2-stable-diffusion", 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
- Xet hash:
- 18826cb7dceb0dfd9e65c91bb77334ad4d85002d205bd0c1730c9eb31f4d8b79
- Size of remote file:
- 246 MB
- SHA256:
- 73655360ca6076071cf6f6fd1435de80d8c2ee6b271c7fdb2c79d7de351efb44
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