Instructions to use Magifactory/t-shirt_diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Magifactory/t-shirt_diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Magifactory/t-shirt_diffusion", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from Magifactory/t-shirt_diffusion: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/Magifactory/t-shirt_diffusion/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://Magifactory/t-shirt_diffusion/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Magifactory/t-shirt_diffusion/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- ecf0d53ffa447f736da0b425294e8626ad1cb83e18be4b4c7466ecf61c732bfb
- Size of remote file:
- 492 MB
- SHA256:
- dcb7bb3bf76c7b24d85f80adf2627adba3a8a5fd4500f71265e54e4f7b212bfd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.