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:
- 6748bd3401a80a4f017b13abdc2c349f14d3ca5dfd89e504988fcd294c1cf0be
- Size of remote file:
- 4.09 kB
- SHA256:
- 25135e894ce93ba1c5a793e95ff8160af0d169d25718ee0c09c7198cd1c05eeb
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