Instructions to use Joshua-Abok/bifold-windows with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Joshua-Abok/bifold-windows with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Joshua-Abok/bifold-windows", 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 Joshua-Abok/bifold-windows: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/Joshua-Abok/bifold-windows/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://Joshua-Abok/bifold-windows/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Joshua-Abok/bifold-windows/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- d017f7c7e58525c43c95c4c1e5ddfa9ac80fddbbc53dae2849d4f49ffaffa842
- Size of remote file:
- 246 MB
- SHA256:
- 9f1c5f7f4062f06ed032d73337907336b0c856a7fd8700cc65f96e0b85cced35
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