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:
- ea49dbe9607e6fc377163f30d6456cf3702006769c98a889e8285da387453e15
- Size of remote file:
- 3.46 GB
- SHA256:
- 34761192e5c58452b3ee5af7b6feccf667f657881054fb103dd7e89292ac45d1
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