Instructions to use JPeace18/CarIdentifier2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JPeace18/CarIdentifier2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="JPeace18/CarIdentifier2") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("JPeace18/CarIdentifier2") model = AutoModelForImageClassification.from_pretrained("JPeace18/CarIdentifier2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Image Classification
Validation Metricsg
loss: 5.987339019775391
f1_macro: 0.014272821191130344
f1_micro: 0.049443212901385813
f1_weighted: 0.024064270485240995
precision_macro: 0.021826631000654732
precision_micro: 0.049443212901385813
precision_weighted: 0.03411589816873522
recall_macro: 0.02794951571811764
recall_micro: 0.049443212901385813
recall_weighted: 0.049443212901385813
accuracy: 0.049443212901385813
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