Instructions to use TE2G/MediumThick with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TE2G/MediumThick 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-3-medium-diffusers", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("TE2G/MediumThick") prompt = "A photo of Medium Thick knit pullover on a mannequin or torso" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- f49f043ba5c31c9cc4d8cd6b401220a6423d243acbbf1ae8dbdda0e1c8b748ff
- Size of remote file:
- 9.6 MB
- SHA256:
- 702ed122acb40199dac1e148bdda5e98ddd0255d2984e18e759ed5ab3845ef4e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.