Instructions to use ibombonato/swin-age-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ibombonato/swin-age-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ibombonato/swin-age-classifier") 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("ibombonato/swin-age-classifier") model = AutoModelForImageClassification.from_pretrained("ibombonato/swin-age-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ibombonato/swin-age-classifier: direct link, hf CLI and curl.
- Browser
- Download file 110 MB
-
https://huggingface.co/ibombonato/swin-age-classifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ibombonato/swin-age-classifier/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ibombonato/swin-age-classifier/resolve/main/pytorch_model.bin
110 MB
- Xet hash:
- fccb0b4b12ce524589eba2795faff0eb56d3a9b014412ea4967cc96938aee4e3
- Size of remote file:
- 110 MB
- SHA256:
- 42d00888d6bfe8709bfd0e84681843b89784e44abc17119d9086b35300059a5a
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