Instructions to use textattack/bert-base-uncased-STS-B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/bert-base-uncased-STS-B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/bert-base-uncased-STS-B")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/bert-base-uncased-STS-B") model = AutoModelForSequenceClassification.from_pretrained("textattack/bert-base-uncased-STS-B") - Notebooks
- Google Colab
- Kaggle
Update eval_results_sts-b.txt
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eval_results_sts-b.txt
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eval_loss = 0.5317465104162693
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eval_pearson = 0.8804623819055606
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eval_spearmanr = 0.8763303317439618
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eval_corr = 0.8783963568247612
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epoch = 3.0
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