Instructions to use aichina/ttz-471 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use aichina/ttz-471 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("aichina/ttz-471", dtype=torch.bfloat16, device_map="cuda") prompt = "ttz" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from aichina/ttz-471: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/aichina/ttz-471/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://aichina/ttz-471/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/aichina/ttz-471/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 25091843c9580e8b75f2304b376f4501ed350e724b70aa74caed80b26057acb9
- Size of remote file:
- 492 MB
- SHA256:
- 8c18b9a569de8fdde916ae6f87b5c8412597e992e6bf415def4e5038a4f1e5ec
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