Instructions to use ForserX/ControlNetMediaPipeFace-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ForserX/ControlNetMediaPipeFace-onnx with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ForserX/ControlNetMediaPipeFace-onnx", 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:
- e4525367e1c50c332e18283da8f058a5149c98df3809c32595bb81e122c6448b
- Size of remote file:
- 724 MB
- SHA256:
- 104ebc6633dae71cf96c0027b4692f6228a2eb4d9f9a4ccaa7badba0c6c0a448
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