Instructions to use victor/autotrain-satellite-image-classification-40975105875 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use victor/autotrain-satellite-image-classification-40975105875 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="victor/autotrain-satellite-image-classification-40975105875") 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("victor/autotrain-satellite-image-classification-40975105875") model = AutoModelForImageClassification.from_pretrained("victor/autotrain-satellite-image-classification-40975105875", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 40975105875
- CO2 Emissions (in grams): 2.3260
Validation Metrics
- Loss: 0.002
- Accuracy: 1.000
- Macro F1: 1.000
- Micro F1: 1.000
- Weighted F1: 1.000
- Macro Precision: 1.000
- Micro Precision: 1.000
- Weighted Precision: 1.000
- Macro Recall: 1.000
- Micro Recall: 1.000
- Weighted Recall: 1.000
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