Instructions to use cuongdev/2nguoiv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/2nguoiv2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cuongdev/2nguoiv2", 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:
- f53a5e47c26bbfdf9e4aee209c2ecd76b33047597d13590afa40f2cc6fedc122
- Size of remote file:
- 681 MB
- SHA256:
- 11ef64832545c0181a0eb5050b6696adeae3d27c9fa1e0c4855a208f304ddeec
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