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
| { | |
| "epoch": 8.0, | |
| "eval_accuracy": 0.9730591259640102, | |
| "eval_f1_macro": 0.9727023139698624, | |
| "eval_loss": 0.11002838611602783, | |
| "eval_runtime": 216.4171, | |
| "eval_samples_per_second": 134.809, | |
| "eval_steps_per_second": 8.428, | |
| "eval_top5_accuracy": 0.996846615252785 | |
| } |