Instructions to use procodomatic/food_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use procodomatic/food_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="procodomatic/food_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("procodomatic/food_classifier") model = AutoModelForImageClassification.from_pretrained("procodomatic/food_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from procodomatic/food_classifier: direct link, hf CLI and curl.
- Browser
- Download file 344 MB
-
https://huggingface.co/procodomatic/food_classifier/resolve/main/tf_model.h5
- Command line
-
hf download hf://procodomatic/food_classifier/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/procodomatic/food_classifier/resolve/main/tf_model.h5
344 MB
- Xet hash:
- 608f4ba1a284e2e1754ff7a8616e79bdb03f11e7478edefeaf2ab4a5e18e4ca3
- Size of remote file:
- 344 MB
- SHA256:
- 822f51f61de4fb6c570c1fd88556d267f9272e82e2ff76796914490648a9dce4
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