Image Classification
Transformers
Safetensors
PyTorch
food-recognition
dinov3
vision-transformer
tsotsa-img
Instructions to use anonymous-eval/food-recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anonymous-eval/food-recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="anonymous-eval/food-recognition") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("anonymous-eval/food-recognition", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,699 Bytes
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"run_name": "dinov3_epochs_8",
"model_name": "facebook/dinov3-vitl16-pretrain-lvd1689m",
"model_slug": "facebook-dinov3-vitl16-pretrain-lvd1689m",
"epochs": 8,
"output_dir": "./model_saved/finetuning/facebook-dinov3-vitl16-pretrain-lvd1689m/epochs_8",
"logging_dir": "./finetuning/logs/runs/facebook-dinov3-vitl16-pretrain-lvd1689m/epochs_8",
"cache_dir": "./cached_dataset/finetuning/facebook-dinov3-vitl16-pretrain-lvd1689m",
"started_at": "2026-06-16T11:27:32.527592+00:00",
"train_finished_at": "2026-06-16T21:48:26.431336+00:00",
"finished_at": "2026-06-16T21:52:22.912657+00:00",
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"train_metrics": {
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"total_flos": 0.0,
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"eval_metrics": {
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"eval_accuracy": 0.9730591259640102,
"eval_f1_macro": 0.9727023139698624,
"eval_top5_accuracy": 0.996846615252785,
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"eval_samples_per_second": 134.809,
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"epoch": 8.0
}
} |