Instructions to use heine123/benben_out with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use heine123/benben_out with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("heine123/benben_out") prompt = "a photo of benben cartoon cow,with red skin,cute face,two horns on the head,white cheeks" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 3c09205dadd4b0776b13b1806aa72d46da06db57a7166a7842c7ec93da111965
- Size of remote file:
- 3.29 MB
- SHA256:
- 308db178e575eb1c2463865491aaea181f810ce216e59a768813f48f1bbd23c6
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