Instructions to use c-eshih/human_stable_diffusion_concat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use c-eshih/human_stable_diffusion_concat with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("c-eshih/human_stable_diffusion_concat", 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:
- d3aade1d0030c4b79015bde3e141cd37a981584d42d23af32d067fee2d0b8e1f
- Size of remote file:
- 6.88 GB
- SHA256:
- 7e318335e5fab12e4a48077497eed80bc6c3c8c1fbf9b83abccff91def6ad32b
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