Image Classification
Transformers
TensorBoard
Safetensors
PyTorch
vit
huggingpics
Eval Results (legacy)
Instructions to use MDZN/fruit-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MDZN/fruit-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="MDZN/fruit-classifier") 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("MDZN/fruit-classifier") model = AutoModelForImageClassification.from_pretrained("MDZN/fruit-classifier") - Notebooks
- Google Colab
- Kaggle
fruit-classifier
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
Apple
Banana
Grape
Kiwi
Strawberry
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Evaluation results
- Accuracyself-reported0.964




