Instructions to use Mahmoud7/HFDiffusionOfficial_output_dir_Cond with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Mahmoud7/HFDiffusionOfficial_output_dir_Cond with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Mahmoud7/HFDiffusionOfficial_output_dir_Cond", 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
- Xet hash:
- 635abf8a09f00477ac2740ef9b20ee0f893d51243845d46bcc3197ebbf418451
- Size of remote file:
- 73.3 MB
- SHA256:
- 8474e0efba0ecee30b41d5d6cc9103d84bc660c2d9fdab2713b21faaaacfca22
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