Image Classification
Transformers
TensorBoard
Safetensors
vit
food
fruits
junkfood
Generated from Trainer
Instructions to use gutkia01/vit-food-classification-gutkia01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gutkia01/vit-food-classification-gutkia01 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="gutkia01/vit-food-classification-gutkia01") 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("gutkia01/vit-food-classification-gutkia01") model = AutoModelForImageClassification.from_pretrained("gutkia01/vit-food-classification-gutkia01", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model save
Browse files- README.md +1 -5
- model.safetensors +1 -1
README.md
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license: apache-2.0
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base_model: google/vit-base-patch16-224
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tags:
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- image-classification
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- food
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- fruits
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- junkfood
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model-index:
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- name: vit-food-classification-gutkia01
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# vit-food-classification-gutkia01
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the
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## Model description
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license: apache-2.0
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base_model: google/vit-base-patch16-224
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tags:
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- generated_from_trainer
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model-index:
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- name: vit-food-classification-gutkia01
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# vit-food-classification-gutkia01
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the None dataset.
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## Model description
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model.safetensors
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