Instructions to use Johnhex/Clam with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Johnhex/Clam with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Johnhex/Clam", 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:
- dbcdbbeec7d5c19ff71b419c8fed85c02e2c737b83dc9aec049e2bb112c4d46e
- Size of remote file:
- 492 MB
- SHA256:
- ba834df212216d6efd9dc1ef37fd06666d2ad4f15e38a1a8b99309e1032887fe
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