Instructions to use davanstrien/autotrain-wikiart-sample2-42615108993 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davanstrien/autotrain-wikiart-sample2-42615108993 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="davanstrien/autotrain-wikiart-sample2-42615108993") 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("davanstrien/autotrain-wikiart-sample2-42615108993") model = AutoModelForImageClassification.from_pretrained("davanstrien/autotrain-wikiart-sample2-42615108993") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 42615108993
- CO2 Emissions (in grams): 11.2052
Validation Metrics
- Loss: 0.761
- Accuracy: 0.729
- Macro F1: 0.682
- Micro F1: 0.729
- Weighted F1: 0.723
- Macro Precision: 0.742
- Micro Precision: 0.729
- Weighted Precision: 0.726
- Macro Recall: 0.658
- Micro Recall: 0.729
- Weighted Recall: 0.729
- Downloads last month
- 3