Image Classification
Transformers
PyTorch
TensorBoard
mobilenet_v2
Generated from Trainer
Eval Results (legacy)
Instructions to use merve/vit-mobilenet-beans-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use merve/vit-mobilenet-beans-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="merve/vit-mobilenet-beans-224") 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("merve/vit-mobilenet-beans-224") model = AutoModelForImageClassification.from_pretrained("merve/vit-mobilenet-beans-224") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6af80d15f0e289c24e8a04e46ec52fe354a717f15a8eb45fb27585cb80bcfb9a
- Size of remote file:
- 9.16 MB
- SHA256:
- af47854d043b59ae961540f6509e5dff1886008d2a4295947d2880abf561fa9f
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