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
- Draw Things
- DiffusionBee
- Xet hash:
- ca5889f28acde68f99c0c694a71bb38a5d6d44e70f4fdffd639cc092fb5dcd43
- Size of remote file:
- 9.6 MB
- SHA256:
- b126393289279e9477c71ae9b13a5ef8e71abc50f3f3c89de96e78d92a394903
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