Instructions to use Mahmoud7/HFDiffusionOfficial_output_dir_Cond_V with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Mahmoud7/HFDiffusionOfficial_output_dir_Cond_V 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_V", 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:
- 96987b3b293855521a4c67ad1ea3faa9a75a7f7a1911504e2c413c5dc64fb6b5
- Size of remote file:
- 563 Bytes
- SHA256:
- 289bdc7c8f764b66f89c7d91c25b2544bfb7e66f32ab30476149139d8e8ad13d
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