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
Download checkpoint-26500/random_states_0.pkl from TE2G/thin: direct link, hf CLI and curl.
- Browser
- Download file 14.5 kB
-
https://huggingface.co/TE2G/thin/resolve/main/checkpoint-26500/random_states_0.pkl
- Command line
-
hf download hf://TE2G/thin/checkpoint-26500/random_states_0.pkl
-
curl -L -o random_states_0.pkl https://huggingface.co/TE2G/thin/resolve/main/checkpoint-26500/random_states_0.pkl
14.5 kB
- Xet hash:
- a2547ac79907a80e83978581012683beaf8477f8c18cde16d66ca97a760ddf36
- Size of remote file:
- 14.5 kB
- SHA256:
- fac76147c60247af2cb801c758a03160117193d18afc577babbe2369eb8344af
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.