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
- Xet hash:
- f95ad5196f56a8b127a303e57f345d816c6895af61864e9c52ab6dbcafa9d259
- Size of remote file:
- 1.6 MB
- SHA256:
- e5941cc94cb6e61f79a00830562beb2356b174bda58772243d6b8fef29407777
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