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:
- 78636dfb15f01ca6d347effd5e45ec99f17044e47deabfadd1d5a6f5247cfeda
- Size of remote file:
- 3.49 MB
- SHA256:
- 43f69fd9d957c78f64a0f2c85f8cdd49f174135de9e6833849c3a865dd544baf
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.