Instructions to use textattack/distilbert-base-cased-QQP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/distilbert-base-cased-QQP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/distilbert-base-cased-QQP")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/distilbert-base-cased-QQP") model = AutoModelForSequenceClassification.from_pretrained("textattack/distilbert-base-cased-QQP") - Notebooks
- Google Colab
- Kaggle
Update eval_results_qqp.txt
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eval_results_qqp.txt
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eval_loss = 0.2876177510715243
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eval_acc = 0.8974771209497897
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eval_f1 = 0.8627437994635584
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eval_acc_and_f1 = 0.880110460206674
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epoch = 3.0
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