Instructions to use satani/TI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use satani/TI with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("satani/TI", 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 satani/TI: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/satani/TI/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://satani/TI/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/satani/TI/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 338f90ef835ee8985713737bd4f9160a69e2db1d01667e207c6cd88223e5fb75
- Size of remote file:
- 492 MB
- SHA256:
- b3f4d0893d43596adb66e0ea3e8429a14ecd2933facf38f2e5af0a98df369121
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.