Instructions to use Samit/samit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Samit/samit with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Samit/samit", 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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- bf589cb8fdd1398cb5e8e4a2d20429337f6b9e97a931f4f3f51ef5730ffcfa54
- Size of remote file:
- 246 MB
- SHA256:
- 7cf8d690513f92f9b1c54dc97d781c2e1973c849adccba8a89cceb0b7a52074c
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