Instructions to use Squirz/phase with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Squirz/phase with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Squirz/phase", 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 unet/diffusion_pytorch_model.bin from Squirz/phase: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/Squirz/phase/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://Squirz/phase/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/Squirz/phase/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- 53761865958870c5a20a374191e729d5f848ece6bcf8c08e7a2ac0f1ab95bbf6
- Size of remote file:
- 3.44 GB
- SHA256:
- ae471b8b6ade981f490b2903223c9cb29a82cfc1cad32bd4a7bb5107612d726d
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