Instructions to use DejanX13/vit-house-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DejanX13/vit-house-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="DejanX13/vit-house-classifier") 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("DejanX13/vit-house-classifier") model = AutoModelForImageClassification.from_pretrained("DejanX13/vit-house-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload eval_results.json with huggingface_hub
Browse files- eval_results.json +5 -5
eval_results.json
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"eval_accuracy": 0.8125,
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"eval_loss": 0.5628954172134399,
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"eval_runtime": 1.3791,
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"eval_samples_per_second": 58.007,
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"eval_steps_per_second": 7.251
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