Instructions to use Dhika/raildefect5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dhika/raildefect5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Dhika/raildefect5") 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("Dhika/raildefect5") model = AutoModelForImageClassification.from_pretrained("Dhika/raildefect5") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 40
Browse files
pytorch_model.bin
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runs/Jun01_00-46-53_08b47cf99abe/events.out.tfevents.1685580426.08b47cf99abe.22772.0
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