Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use ruben09/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ruben09/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ruben09/image_classification") 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("ruben09/image_classification") model = AutoModelForImageClassification.from_pretrained("ruben09/image_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files
config.json
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"problem_type": "single_label_classification",
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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.44.
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}
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"problem_type": "single_label_classification",
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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.44.0"
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}
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model.safetensors
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runs/Sep06_05-31-36_3e67937702a2/events.out.tfevents.1725600717.3e67937702a2.36.0
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runs/Sep06_05-31-36_3e67937702a2/events.out.tfevents.1725600817.3e67937702a2.36.1
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training_args.bin
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size 5240
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