Instructions to use Moreza009/HF_CVcourse_FoodClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Moreza009/HF_CVcourse_FoodClassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Moreza009/HF_CVcourse_FoodClassifier") 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("Moreza009/HF_CVcourse_FoodClassifier") model = AutoModelForImageClassification.from_pretrained("Moreza009/HF_CVcourse_FoodClassifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Moreza009/HF_CVcourse_FoodClassifier: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/Moreza009/HF_CVcourse_FoodClassifier/resolve/main/training_args.bin
- Command line
-
hf download hf://Moreza009/HF_CVcourse_FoodClassifier/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/Moreza009/HF_CVcourse_FoodClassifier/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- be3cdfd3220f5ffabc64b6d4808401ab4cd142b9cf16903982a14064143b7456
- Size of remote file:
- 5.18 kB
- SHA256:
- 52ae6160004714c815ba25e1872f3e3ac3bec9e2e7c0dcc51727c32d29ade64c
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