Instructions to use Johnhex/Clam1.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Johnhex/Clam1.1 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/Clam1.1", 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:
- 9fdc09555c9f0be98d381a09d56af01919256cbbb98c3454365f96ebc311e481
- Size of remote file:
- 335 MB
- SHA256:
- 257acbd51ccf1b997c1eacc6485ea8a53e06465df1ed9511678fc30b0fd530f4
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