Instructions to use eristotelian/simlora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use eristotelian/simlora 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("eristotelian/simlora") prompt = "simlora" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- bfac85c1ee5a0056d5c1adf9c041b38c5dcd079e42995a0e139d4bc6e5184c8a
- Size of remote file:
- 4 MB
- SHA256:
- 6d5aaa7a6a307e0abe6eee167e3ab61195ab951e6c3543872c136a12a77e78d5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.