Instructions to use cuongdev/nmthu-v10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/nmthu-v10 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/nmthu-v10", 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:
- 207bba72f4e3108b76f088aae3fd7f8f5df0a96684e8f81582337cc59bfbc88c
- Size of remote file:
- 681 MB
- SHA256:
- 664b7303f04c3a0001eed1aa7c78d6b6e86f250f0b99ea44ea4d8b18915aefed
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