pritamdeka
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BioBert-PubMed200kRCT

Text Classification

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pritamdeka commited on Jul 23, 2022

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1 Parent(s): 09ff0af

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@@ -38,8 +38,8 @@ The model can be directly used like this:
 ```python
 from transformers import TextClassificationPipeline
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
-model = AutoModelForSequenceClassification.from_pretrained("pritamdeka/PubMedBert-PubMed200kRCT")
-tokenizer = AutoTokenizer.from_pretrained("pritamdeka/PubMedBert-PubMed200kRCT")
 pipe = TextClassificationPipeline(model=model, tokenizer=tokenizer, return_all_scores=True)
 pipe("Treatment of 12 healthy female subjects with CDCA for 2 days resulted in increased BAT activity.")
 ```

 ```python
 from transformers import TextClassificationPipeline
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
+model = AutoModelForSequenceClassification.from_pretrained("pritamdeka/BioBert-PubMed200kRCT")
+tokenizer = AutoTokenizer.from_pretrained("pritamdeka/BioBert-PubMed200kRCT")
 pipe = TextClassificationPipeline(model=model, tokenizer=tokenizer, return_all_scores=True)
 pipe("Treatment of 12 healthy female subjects with CDCA for 2 days resulted in increased BAT activity.")
 ```