Instructions to use Prompsit/paraphrase-bert-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prompsit/paraphrase-bert-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Prompsit/paraphrase-bert-en")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Prompsit/paraphrase-bert-en") model = AutoModelForSequenceClassification.from_pretrained("Prompsit/paraphrase-bert-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -37,7 +37,7 @@ logits = model(**input).logits
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soft = torch.nn.Softmax(dim=1)
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print(soft(logits))
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```
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```
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tensor([[0.1592, 0.8408]], grad_fn=<SoftmaxBackward>)
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```
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soft = torch.nn.Softmax(dim=1)
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print(soft(logits))
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```
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Code output is:
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```
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tensor([[0.1592, 0.8408]], grad_fn=<SoftmaxBackward>)
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```
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