Instructions to use jinofcoolnes/sammod with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jinofcoolnes/sammod with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jinofcoolnes/sammod", 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:
- 990a3c5574a9917e405371db5ed2882c916eef32df0bc1fe34dba76c292ea2a9
- Size of remote file:
- 492 MB
- SHA256:
- 2f91a6d45ee5ed7cb7022f6e9830446fd3cae1352f9020b4eba1189780d45922
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