Instructions to use codecandy/antiblur with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codecandy/antiblur with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("codecandy/antiblur") prompt = "a young college student, walking on the street, campus background, photography" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download poster.jpg from codecandy/antiblur: direct link, hf CLI and curl.
- Browser
- Download file 1.6 MB
-
https://huggingface.co/codecandy/antiblur/resolve/main/poster.jpg
- Command line
-
hf download hf://codecandy/antiblur/poster.jpg
-
curl -L -o poster.jpg https://huggingface.co/codecandy/antiblur/resolve/main/poster.jpg
1.6 MB

- Xet hash:
- 46e3266900e761c94f20e4065b8a266551eb6ce82022556beb2bdff3ef1a5afc
- Size of remote file:
- 1.6 MB
- SHA256:
- 3f57b5073c4c2fde9ee0aef69de838aa057233b985209b57974c616e9c46cc96
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