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:
- 21230fc41a932b141b0fe187fe82408ef035f0de2bbef00f064f786f05fb4853
- Size of remote file:
- 2.13 GB
- SHA256:
- f192324b842fa94011426023c6065d7611fe5a3d8185adf2f2a962944656cce7
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