Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use rriverar75/vit-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rriverar75/vit-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="rriverar75/vit-model") 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("rriverar75/vit-model") model = AutoModelForImageClassification.from_pretrained("rriverar75/vit-model") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 87ffa58
update model card README.md
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README.md
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license: apache-2.0
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base_model: google/vit-base-patch16-224-in21k
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tags:
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- generated_from_trainer
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datasets:
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- beans
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license: apache-2.0
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base_model: google/vit-base-patch16-224-in21k
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tags:
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- image-classification
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- generated_from_trainer
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datasets:
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- beans
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