Instructions to use nawed/nawed-new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nawed/nawed-new with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nawed/nawed-new", 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:
- 433a9ee13d979f2b4e2d6890cb548c7cfb10a00123854fb76c1eb70cd19725f7
- Size of remote file:
- 492 MB
- SHA256:
- 56e35f2a4591f02785b8ead200582e47e1dd4687c07396ed73b7c49def980df9
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