Instructions to use daeunni/exp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use daeunni/exp 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/exp") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- e64555c2cdc6f6213afcaa65772c86902351d240635d964bc14c18f513503c49
- Size of remote file:
- 6.59 MB
- SHA256:
- 7e6fd5a664e89336afbf4518958df359d9282ec04be5e528a48e4f7f2b0bc9fc
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