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:
- de07f91f689b4aeb2b9038d4f3375fccd4612c15b11398f3497825b516edc22b
- Size of remote file:
- 3.44 GB
- SHA256:
- 0bda4fe90c6c7f6bd391a301f8866c0269c7ac63cdd6ba6e7e29769583f0aeae
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