Instructions to use shellypeng/AtomicXL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use shellypeng/AtomicXL with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("shellypeng/AtomicXL", torch_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:
- a9a8e463f4b98f125985d9dfe18b9b804e4959b6b9bfa9903c370e4d25aa777c
- Size of remote file:
- 246 MB
- SHA256:
- ed456908b268f08ba11553eeaa2eb891c07ebf1d5e3d0bf049c93ee55f6794f2
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