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")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("msmsming/Food_test") model = AutoModelForImageClassification.from_pretrained("msmsming/Food_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Food_test
Autogenerated by HuggingPics๐ค๐ผ๏ธ
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
- Downloads last month
- 6
Space using msmsming/Food_test 1
Evaluation results
- Accuracyself-reported0.900



