Instructions to use broidkhegde/hegde with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use broidkhegde/hegde with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("broidkhegde/hegde", 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 broidkhegde/hegde: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/broidkhegde/hegde/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://broidkhegde/hegde@refs/pr/2/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/broidkhegde/hegde/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 018ff034cdf73ec7fd0dd4d428ecdefdd275de3db54af02ee6fcc1f3f0e49d83
- Size of remote file:
- 246 MB
- SHA256:
- 55b7168ee863e72339b3cc1779f062b479c1f4cdf29da4a9dab24ce11e5d1c0a
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