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:
- c1a617294ef1591f65a42ac2a8e2b42e228d00b80bce9bca4211bfd8019e0a4c
- Size of remote file:
- 3.46 GB
- SHA256:
- f779112bda8900ebac4f830cf6216e1b7301614913bc98a2c9444f8134557927
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