Image Classification
Transformers
TensorBoard
Safetensors
PyTorch
vit
huggingpics
Eval Results (legacy)
Instructions to use msmsming/Food_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use msmsming/Food_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="msmsming/Food_test") 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("msmsming/Food_test") model = AutoModelForImageClassification.from_pretrained("msmsming/Food_test") - Notebooks
- Google Colab
- Kaggle
Food_test
Autogenerated by HuggingPics🤗🖼️
Create your own image classifier for anything by running the demo on Google Colab.
Report any issues with the demo at the github repo.
Example Images
pasta
pizza
salad
taco
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Space using msmsming/Food_test 1
Evaluation results
- Accuracyself-reported0.900



