Instructions to use Thamer/vit-base-fine_tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Thamer/vit-base-fine_tuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Thamer/vit-base-fine_tuned") 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("Thamer/vit-base-fine_tuned") model = AutoModelForImageClassification.from_pretrained("Thamer/vit-base-fine_tuned") - Notebooks
- Google Colab
- Kaggle
Commit History
Training in progress, epoch 10 afea641
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Training in progress, epoch 9 0fe7286
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Training in progress, epoch 8 d6a4772
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Training in progress, epoch 7 1c6bd3f
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Training in progress, epoch 6 30d2f7e
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Training in progress, epoch 5 7879bdb
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Training in progress, epoch 4 2ff6c73
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Training in progress, epoch 3 e01fd8f
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Training in progress, epoch 2 d5e7c8c
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Training in progress, epoch 1 e3ae387
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initial commit 0eb595b
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