Instructions to use stablediffusionapi/controlnet-animeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/controlnet-animeline with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stablediffusionapi/controlnet-animeline", 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
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 615b80eae63eea07d5cc8b709a0cf890175b9f51dcadb1054efa6ceea6540002
- Size of remote file:
- 1.45 GB
- SHA256:
- d53620133ce3383a4e66cc34623d33a4c7e48b6ed1a8faf683fce60647010100
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