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:
- 5475e368975590360df21d318d9801704c7d7491df680deaf9512009a68b0f4d
- Size of remote file:
- 563 Bytes
- SHA256:
- 0007f0636029b6d89afd70838fd442d61960d536b4a3e683b6bd6eec76443bf6
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