Instructions to use galbitang/autotrain-sofa_style_classification-94412146080 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use galbitang/autotrain-sofa_style_classification-94412146080 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="galbitang/autotrain-sofa_style_classification-94412146080") 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("galbitang/autotrain-sofa_style_classification-94412146080") model = AutoModelForImageClassification.from_pretrained("galbitang/autotrain-sofa_style_classification-94412146080") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 94412146080
- CO2 Emissions (in grams): 3.4207
Validation Metrics
- Loss: 0.863
- Accuracy: 0.722
- Macro F1: 0.660
- Micro F1: 0.722
- Weighted F1: 0.711
- Macro Precision: 0.720
- Micro Precision: 0.722
- Weighted Precision: 0.735
- Macro Recall: 0.667
- Micro Recall: 0.722
- Weighted Recall: 0.722
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