Instructions to use afshr/norm_CAM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use afshr/norm_CAM with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("afshr/norm_CAM", 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
- Xet hash:
- c2f198b708749d92823e17633fe70e024ea3cfb77990b3d857189aa524a7eec0
- Size of remote file:
- 143 MB
- SHA256:
- a1cadcc1f24953b4d41d3748a129952406e495d1e7900b0c8830486d5b0dc36a
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