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:
- 585938613ce1a2cb66ba04dff30000bc0204d9a18fa4f487678825e21decf524
- Size of remote file:
- 73.3 MB
- SHA256:
- c434174f47b6b64bbe74c86e387c0a31be1f470a6c52e642845817014ccb8293
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