Instructions to use duja1/toni with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use duja1/toni with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("duja1/toni", dtype=torch.bfloat16, device_map="cuda") prompt = "t123oni" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from duja1/toni: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/duja1/toni/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://duja1/toni@refs/pr/2/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/duja1/toni/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 44568ee55937a07d8c27503d8da87835abbedc9e45662f2d306df76d4c0558e6
- Size of remote file:
- 492 MB
- SHA256:
- 3b57ee463505de1dbe203e3286ca2dc92c5250556b5e6aae6c8ba54b85aac13e
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