Instructions to use antonellaavad/jamie with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use antonellaavad/jamie with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1-base", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("antonellaavad/jamie") prompt = "photo of jsd" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 5866ba84214c6b86ac87e7c5637d904776d899f69c0b80cde61da9e6f1c412fa
- Size of remote file:
- 3.42 MB
- SHA256:
- da1b04b41e47d15db309a5446e04df1ca454b120d2c26de7e50b13a6891ca7b5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.