Instructions to use seige-ml/my_awesome_food_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seige-ml/my_awesome_food_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="seige-ml/my_awesome_food_model") 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("seige-ml/my_awesome_food_model") model = AutoModelForImageClassification.from_pretrained("seige-ml/my_awesome_food_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from seige-ml/my_awesome_food_model: direct link, hf CLI and curl.
- Browser
- Download file 4.47 kB
-
https://huggingface.co/seige-ml/my_awesome_food_model/resolve/main/training_args.bin
- Command line
-
hf download hf://seige-ml/my_awesome_food_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/seige-ml/my_awesome_food_model/resolve/main/training_args.bin
4.47 kB
- Xet hash:
- 21967bb575f76b2b6ca48bd7c6bcfebdc62d151341370ffc6920d0fd0035f80c
- Size of remote file:
- 4.47 kB
- SHA256:
- 60afa6cb260efe44c1c160582b4ec3520c54c3f31f9dd581db6fc5246bd65a65
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