Instructions to use heesun1/difu_model_2000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use heesun1/difu_model_2000 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("heesun1/difu_model_2000", 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:
- 360a047dfadab3daaca9d67b9d8fde794c770d545c106e0b2fc13e38f608117e
- Size of remote file:
- 6.93 GB
- SHA256:
- dbe3a4be454487c252f91dd643156e78b231989cddc3fd399495347cffa8ea44
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