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, | |
| "run_wall_time_hours": 10.413995842536291, | |
| "run_wall_time_minutes": 624.8397505521774, | |
| "run_wall_time_seconds": 37490.385033130646, | |
| "total_flos": 0.0, | |
| "train_loss": 0.37596295774437, | |
| "train_runtime": 37253.6996, | |
| "train_samples_per_second": 56.386, | |
| "train_steps_per_second": 3.524, | |
| "train_wall_time_hours": 10.348306588000721, | |
| "train_wall_time_minutes": 620.8983952800432, | |
| "train_wall_time_seconds": 37253.9037168026 | |
| } |