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:
- e2602665b46c0d877ed48b0c715e4b0ea68152fd38f21a9937373d1cd8904707
- Size of remote file:
- 3.29 MB
- SHA256:
- 90c0ca7df167f7caf489a876a86dac5f37e954e7c4b710a412c0da97bfe1929d
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