lighteternal
/

BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-mnli

Text Classification

textual-entailment

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lighteternal commited on Oct 27, 2021

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@@ -23,7 +23,7 @@ You can test the model using the HuggingFace model widget on the side:
 - The model returns the probabilities of 3 labels: entailment(LABEL:0), neutral(LABEL:1) and contradiction(LABEL:2) respectively.
 To use the model locally on your machine:
-```
 # import torch
 # device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

 - The model returns the probabilities of 3 labels: entailment(LABEL:0), neutral(LABEL:1) and contradiction(LABEL:2) respectively.
 To use the model locally on your machine:
+```python
 # import torch
 # device = torch.device("cuda" if torch.cuda.is_available() else "cpu")