Instructions to use fusing/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fusing/test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fusing/test", 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.fp16.bin from fusing/test: direct link, hf CLI and curl.
- Browser
- Download file 1.12 GB
-
https://huggingface.co/fusing/test/resolve/refs%2Fpr%2F4/text_encoder/pytorch_model.fp16.bin
- Command line
-
hf download hf://fusing/test@refs/pr/4/text_encoder/pytorch_model.fp16.bin
-
curl -L -o pytorch_model.fp16.bin https://huggingface.co/fusing/test/resolve/refs%2Fpr%2F4/text_encoder/pytorch_model.fp16.bin
1.12 GB
- Xet hash:
- 585c02f10d97f0edae2fdf30858864103fb09e62ecd46cda64b19d0a4c77ca1b
- Size of remote file:
- 1.12 GB
- SHA256:
- 802c4f846a47864170a8f2d60e2b8363bbbe3dac7b2b1a05a2b2fea07291a582
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