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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- a2adf80f249158ec05205b3a400c1a5528efda56a24e64a721343ab546ded1fc
- Size of remote file:
- 6.59 MB
- SHA256:
- d32498f34e23548a2ae6a00a133b6da61fe687bc74f6955d68049a6b2ea444d5
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