Instructions to use cuongdev/vtthuc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/vtthuc 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/vtthuc", 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:
- 9a4c44bf840835cae7edfbb09367f89e39536cb738b57ffe552816c5ef23608f
- Size of remote file:
- 2.61 GB
- SHA256:
- 037282e3f7fa2b7450fdaaa461a425c79df668a721de15eb93767cdb2a4e4009
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