Instructions to use Efimov6886/row4_98 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Efimov6886/row4_98 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Efimov6886/row4_98") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Efimov6886/row4_98", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 2477076728
- CO2 Emissions (in grams): 1.8937
Validation Metrics
- Loss: 0.047
- Accuracy: 0.980
- Macro F1: 0.980
- Micro F1: 0.980
- Weighted F1: 0.980
- Macro Precision: 0.980
- Micro Precision: 0.980
- Weighted Precision: 0.980
- Macro Recall: 0.980
- Micro Recall: 0.980
- Weighted Recall: 0.980
- Downloads last month
- 8