Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use nickmuchi/vit-base-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nickmuchi/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nickmuchi/vit-base-beans") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("nickmuchi/vit-base-beans") model = AutoModelForImageClassification.from_pretrained("nickmuchi/vit-base-beans", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add verifyToken field to verify evaluation results are produced by Hugging Face's automatic model evaluatorโ
Beep boop, I am a bot from Hugging Face's automatic model evaluator ๐! We've added a new `verifyToken` field to your evaluation results to verify that they are produced by the model evaluator. Accept this PR to ensure that your results remain listed as **verified** on the [Hub leaderboard](https://huggingface.co/spaces/autoevaluate/leaderboards).4286753
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Add evaluation results on beans dataset (#1)โ
- Add evaluation results on beans dataset (e9fa39080e74fd45eccf4a6053cf2d0cdacf5155) Co-authored-by: Evaluation Bot <autoevaluator@users.noreply.huggingface.co>ce033b1
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Update README.mdโ
Added examples88472f8 -
update model card README.md
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๐ป cheers
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Model save
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Training in progress, step 500
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Training in progress, step 300
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Training in progress, step 100
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initial commit
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