Instructions to use daeunni/teddybear with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use daeunni/teddybear with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("daeunni/teddybear") prompt = "a photo of sks teddybear" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 9060d2246231c5bf8ee14a66b7eb821ba5c6b81d444bf0152d71e7cca517d9cc
- Size of remote file:
- 6.59 MB
- SHA256:
- 81c5f7e41d67a2ceb8ae4b058daeba6175567f7824e78d79daf0ff8b0eaa3adf
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