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", torch_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:
- 792149f42f95e88d8e725f0e9dbbd812d8ceaf1e0d0732a8a203e3a84dd5f970
- Size of remote file:
- 9.6 MB
- SHA256:
- 3098aa52f229e913d60747458411c9508912f888f87af2a7e6c7ff17b7ee6f9b
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