Instructions to use JCTN/controlnet-segment-anything with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JCTN/controlnet-segment-anything with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("JCTN/controlnet-segment-anything", 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:
- 5732a7d8ce3c55c48a14838af8626773f05d257a7aee4d2b7415f7e568fea803
- Size of remote file:
- 1.45 GB
- SHA256:
- 9d4f35bb941e35ceeb54e4d6d35c9239949b193e5c7389426b95a97e43de884d
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