Instructions to use cuongdev/5nguoi-5000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/5nguoi-5000 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/5nguoi-5000", 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:
- a311805ca49a8f628a9ff8399c4be8f00d02d33f888e01282bb75da30f91d0f5
- Size of remote file:
- 681 MB
- SHA256:
- efcc273a1f151dea853b0c7d19018145c671e90ca67c4b0c6f03da98a87b93b4
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