Instructions to use textattack/bert-base-uncased-QQP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/bert-base-uncased-QQP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/bert-base-uncased-QQP")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/bert-base-uncased-QQP") model = AutoModelForSequenceClassification.from_pretrained("textattack/bert-base-uncased-QQP") - Inference
- Notebooks
- Google Colab
- Kaggle
Update eval_results_qqp.txt
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eval_results_qqp.txt
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eval_loss = 0.24866826211314508
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eval_acc = 0.9090774177590898
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eval_f1 = 0.8781813361611877
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eval_acc_and_f1 = 0.8936293769601387
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epoch = 3.0
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