Instructions to use antonellaavad/leggregator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use antonellaavad/leggregator 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/leggregator") prompt = "Representative" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 836f7644b943352a70d1b7199d2491dfc33da304e8d6c99b6cd198514690173a
- Size of remote file:
- 3.42 MB
- SHA256:
- 18965cbe7039d45e9faa1cdde59ebf9cd20d4d62992f1a15481d8fcd4cc92026
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.