Instructions to use adhisetiawan/vit-base-patch16-224-finetuned-food102 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adhisetiawan/vit-base-patch16-224-finetuned-food102 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="adhisetiawan/vit-base-patch16-224-finetuned-food102") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("adhisetiawan/vit-base-patch16-224-finetuned-food102") model = AutoModelForImageClassification.from_pretrained("adhisetiawan/vit-base-patch16-224-finetuned-food102", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81521aa420a6f0dddc8afb1dcf1049075ef6cfdb9ba6f890431938db4abe1309
- Size of remote file:
- 5.24 kB
- SHA256:
- 9bc66fdf568ff57fec9c82b4c5f1c42dae12a6a092b090336f962e9e03979434
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