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:
- 23e8837ce1b5e3880331819d2df193ad04c1ce0accfabfe67aad04197adba769
- Size of remote file:
- 3.46 GB
- SHA256:
- 2bd3fc3e1cf5282620fdf7ace6fba4d63c6d7300953381a7356df6963feca2b4
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