Instructions to use matgu23/ntrlph with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use matgu23/ntrlph with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("matgu23/ntrlph", 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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 2189463d6d9a21a073ad02ec600b25333900047ee64b9cc5b3a6ef88f22a4d56
- Size of remote file:
- 246 MB
- SHA256:
- a1eab1f29bf5c9e40e7625c95bf666f8cf488015ff65fbf94ab8968ae2c82c19
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