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")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Arro94/nova-model-benchmark") model = AutoModelForSequenceClassification.from_pretrained("Arro94/nova-model-benchmark") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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pipeline_tag: text-classification
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Scores (avg. weighted) |
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Accuracy: 0.9007633587786259 |
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Precision: 0.9008606422369183 |
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Recall: 0.9007633587786259 |
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F1: 0.9007595035560719 |
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Hyperparams |
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Max Seq Len: 45 |
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Batch Size: 16 |
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pipeline_tag: text-classification
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Scores (avg. weighted) |
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Accuracy: 0.9007633587786259 |
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Precision: 0.9008606422369183 |
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Recall: 0.9007633587786259 |
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F1: 0.9007595035560719 |
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Hyperparams |
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Max Seq Len: 45 |
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Batch Size: 16 |
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