Instructions to use kxic/eschernet-6dof with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kxic/eschernet-6dof with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kxic/eschernet-6dof", 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:
- f071d55b8227fd500b8150bcbb8278580890ce0944269c82249edfe0ace4954f
- Size of remote file:
- 112 MB
- SHA256:
- 8e6c6b555338aabff48aca39674b78169c826dba20f5a01955fd8138d262d1f7
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