Instructions to use fernandabufon/ft_stable_diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fernandabufon/ft_stable_diffusion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="fernandabufon/ft_stable_diffusion") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("fernandabufon/ft_stable_diffusion") model = AutoModelForImageClassification.from_pretrained("fernandabufon/ft_stable_diffusion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from fernandabufon/ft_stable_diffusion: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/fernandabufon/ft_stable_diffusion/resolve/main/training_args.bin
- Command line
-
hf download hf://fernandabufon/ft_stable_diffusion/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/fernandabufon/ft_stable_diffusion/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 6c0d2e4ff954dab288bebe44a72c502b07481ff145bb14a774153e67760180a6
- Size of remote file:
- 5.3 kB
- SHA256:
- 078aefba1710f20cd3fe504c9d8d7400057b21ac547e891818b557002fc5c440
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