Instructions to use NhatPham/vit-base-patch16-224-recylce-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NhatPham/vit-base-patch16-224-recylce-ft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="NhatPham/vit-base-patch16-224-recylce-ft") 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("NhatPham/vit-base-patch16-224-recylce-ft") model = AutoModelForImageClassification.from_pretrained("NhatPham/vit-base-patch16-224-recylce-ft") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
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by librarian-bot - opened
README.md
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: vit-base-patch16-224
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results: []
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- generated_from_trainer
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metrics:
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- accuracy
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base_model: google/vit-base-patch16-224
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model-index:
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- name: vit-base-patch16-224
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results: []
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