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:
- 037395d1faacc5a06fe54dbaec17372d95224e79e6ee5e1fe4bb120008a4284f
- Size of remote file:
- 563 Bytes
- SHA256:
- b076b0fc8d9d24423b94d5b5702924560e5903ff30a3fa5fb06bd22584d3d87a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.