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:
- e3fe93f9bd9e8f2dfce2fd249f677ef4a425a152613ee5781f236903c879e369
- Size of remote file:
- 9.6 MB
- SHA256:
- b1bd1f3785eba03e56f8ec0da16a6df3b2e8adb316c2a40ad9d3482783edb3ba
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