Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use Dimasnoufal/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dimasnoufal/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Dimasnoufal/image_classification") 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("Dimasnoufal/image_classification") model = AutoModelForImageClassification.from_pretrained("Dimasnoufal/image_classification") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- model.safetensors +1 -1
- runs/Feb09_13-21-53_d4057315a0e6/events.out.tfevents.1707484919.d4057315a0e6.1062.11 +2 -2
- runs/Feb09_13-21-53_d4057315a0e6/events.out.tfevents.1707485624.d4057315a0e6.1062.12 +3 -0
- runs/Feb09_13-34-13_d4057315a0e6/events.out.tfevents.1707485663.d4057315a0e6.1062.13 +3 -0
- training_args.bin +1 -1
model.safetensors
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