Instructions to use mohammadsp99/MyFoodModelViTFull with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mohammadsp99/MyFoodModelViTFull with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mohammadsp99/MyFoodModelViTFull") 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("mohammadsp99/MyFoodModelViTFull") model = AutoModelForImageClassification.from_pretrained("mohammadsp99/MyFoodModelViTFull", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 994f8ef6834c4b637fb5b89d13a252e1587ba73615235e3a5d0fb97023d6e0cb
- Size of remote file:
- 5.11 kB
- SHA256:
- b4f5a870e705b361bda821bfc1b05474993e09edb6322e134db007679fc55c9b
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