Instructions to use cuongdev/tnmthu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/tnmthu 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/tnmthu", 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:
- 48590ed6b154be9c71b097e4d0eaaf3b0c15992f39c489fda30445b2aaa8687b
- Size of remote file:
- 681 MB
- SHA256:
- 0b422bb67111ce5e10b4fe58fcde610a96e501243abecdb8b5fcefd91475941d
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