Instructions to use kushr/duoduo-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kushr/duoduo-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("kushr/duoduo-model") prompt = "duoduo" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 6a097d98a71ee56882a219936b83e4729ebfd5f46977c25e151edf2ca814016f
- Size of remote file:
- 6.53 MB
- SHA256:
- f3fa80930a83999848a6c300bc9bf07daf4094fb7f28cdfe85ad2244e6f245a2
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