Instructions to use Arro94/nova-model-benchmark with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Arro94/nova-model-benchmark with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Arro94/nova-model-benchmark")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Arro94/nova-model-benchmark") model = AutoModelForSequenceClassification.from_pretrained("Arro94/nova-model-benchmark", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Scores (avg. weighted) Accuracy: 0.9007633587786259 Precision: 0.9008606422369183 Recall: 0.9007633587786259 F1: 0.9007595035560719d6514cb -
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Scores (avg. weighted) Accuracy - 0.9007633587786259 F1 - 0.9002557544757034 Precision - 0.9008606422369183 Recall - 0.9007633587786259401599b