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- model.safetensors +1 -1
- runs/Sep06_08-32-08_1b5b8851e47d/events.out.tfevents.1725611537.1b5b8851e47d.612.8 +2 -2
- runs/Sep06_08-32-08_1b5b8851e47d/events.out.tfevents.1725611613.1b5b8851e47d.612.9 +3 -0
- runs/Sep06_08-34-20_1b5b8851e47d/events.out.tfevents.1725611666.1b5b8851e47d.612.10 +3 -0
- training_args.bin +1 -1
model.safetensors
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