Instructions to use cuongdev/vtthuc3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/vtthuc3 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/vtthuc3", 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:
- 88c438d2695759e838c740f2a61d9bbe4d5599e8d206e0ab1ace6ea089240e8a
- Size of remote file:
- 681 MB
- SHA256:
- abe086d85cf1d3f4a3dd323f52d04faf6449817fa1dde1ac87a287b7e51d72a5
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