Instructions to use TE2G/thin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TE2G/thin 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", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("TE2G/thin") prompt = "A photo of thin knit pullover on a mannequin or torso" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- ff8380d6ace91353c2517d0f7520d5be81846e68626f37f0656cca0c46654b34
- Size of remote file:
- 9.6 MB
- SHA256:
- 77ccf650c4ab2eb8f9674ebf781fc922c8dd1f1bee4aea4e73c7e161cf0071c5
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