Instructions to use Suniljl/shru with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Suniljl/shru with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Suniljl/shru", 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 Suniljl/shru: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/Suniljl/shru/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://Suniljl/shru@refs/pr/2/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Suniljl/shru/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 7dbd35f60c9b4a7e24b83ea17aa97bee342156fc5e5850515a8a5780ddf7cb7d
- Size of remote file:
- 246 MB
- SHA256:
- 81f4478f77ea5f00861e0d6630dafd505c13859a5d243e8353db909fc3ac8e96
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