Instructions to use zigg-ai/simomegrietz with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use zigg-ai/simomegrietz with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("zigg-ai/simomegrietz", dtype=torch.bfloat16, device_map="cuda") prompt = "sdcid" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from zigg-ai/simomegrietz: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/zigg-ai/simomegrietz/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://zigg-ai/simomegrietz/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/zigg-ai/simomegrietz/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 11d96c8b17317f2e1810f6d3ef03ba6bd0da52651e78c91deb59c5d7aa5fc476
- Size of remote file:
- 492 MB
- SHA256:
- 168b080074ab6acfc6c1811c9f29b7863a714517e9f425fab6770dcef1af6c4d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.