Instructions to use Efimov6886/row4_accu100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Efimov6886/row4_accu100 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Efimov6886/row4_accu100") 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_accu100", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Configuration Parsing Warning:Config file config.json cannot be fetched (too big)
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 2477076724
- CO2 Emissions (in grams): 0.0039
Validation Metrics
- Loss: 0.021
- Accuracy: 0.990
- Macro F1: 0.990
- Micro F1: 0.990
- Weighted F1: 0.990
- Macro Precision: 0.990
- Micro Precision: 0.990
- Weighted Precision: 0.990
- Macro Recall: 0.990
- Micro Recall: 0.990
- Weighted Recall: 0.990
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