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:
- 8835b02279328a4f5e603a9e1b262b603a6d5b5b4abe456e7f80473ab7706140
- Size of remote file:
- 563 Bytes
- SHA256:
- 683c4d595189439f275ff86902463a3887854c443120795674db59ab836a0bbc
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