Instructions to use lycui/CFSynthesis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lycui/CFSynthesis with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lycui/CFSynthesis", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Champ
How to use lycui/CFSynthesis with Champ:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Commit History
-
Update README.md
Verified signature17a85eb -
upload openpose weights
Verified signature028f539 -
Delete pretrained_weights
Verified signatured8a7076 -
upload openpose weights
Verified signatureb8c895c -
Delete diffusion_pytorch_model.bin
Verified signaturec356fa8 -
upload pretrained weights
Verified signature15b5ca4
-
Update README.md
Verified signature58f8415 -
Create README.md
Verified signaturee487d03 -
Upload pretrained weights
Verified signature4cd2a3a -
initial commit
Verified signature478a8dd