Instructions to use Priyanka-Balivada/stable-diffusion-stack-trial with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Priyanka-Balivada/stable-diffusion-stack-trial with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Priyanka-Balivada/stable-diffusion-stack-trial", 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 Priyanka-Balivada/stable-diffusion-stack-trial: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/Priyanka-Balivada/stable-diffusion-stack-trial/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://Priyanka-Balivada/stable-diffusion-stack-trial/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/Priyanka-Balivada/stable-diffusion-stack-trial/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- a2c7098f1ca89d81c5cc0a5a2178b539505de5155e75188289058903396251d5
- Size of remote file:
- 3.44 GB
- SHA256:
- 5ef0d9cbcb8b449329aa2dba6795282cc9badef88d414039c517668de4341f33
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.