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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- d4aca4d18953086722858443de12736065283433c479765d2547971e9ea3c931
- Size of remote file:
- 3.44 GB
- SHA256:
- 841598c86049f082a12455ff51b5afb1524165b19fa29e1a0ede91d026a91d7e
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