aakorolyova
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reported_outcome_extraction

Token Classification

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aakorolyova commited on May 25, 2022

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1 Parent(s): ea2e252

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@@ -24,7 +24,7 @@ The model should be used with the BioBERT tokeniser. A sample code for getting m
   import numpy as np
   from transformers import AutoTokenizer
   from transformers import AutoModelForTokenClassification
-  from transformers import AutoModelForSequenceClassification
   tokenizer = AutoTokenizer.from_pretrained('dmis-lab/biobert-v1.1')
   model = AutoModelForTokenClassification.from_pretrained(r'aakorolyova/reported_outcome_extraction')
   text = """Compared with placebo plus chemotherapy, pembrolizumab plus chemotherapy improved overall survival in patients with previously untreated, advanced oesophageal squamous cell carcinoma and PD-L1 CPS of 10 or more, and overall survival and progression-free survival in patients with oesophageal squamous cell carcinoma, PD-L1 CPS of 10 or more, and in all randomised patients regardless of histology, and had a manageable safety profile in the total as-treated population."""

   import numpy as np
   from transformers import AutoTokenizer
   from transformers import AutoModelForTokenClassification
   tokenizer = AutoTokenizer.from_pretrained('dmis-lab/biobert-v1.1')
   model = AutoModelForTokenClassification.from_pretrained(r'aakorolyova/reported_outcome_extraction')
   text = """Compared with placebo plus chemotherapy, pembrolizumab plus chemotherapy improved overall survival in patients with previously untreated, advanced oesophageal squamous cell carcinoma and PD-L1 CPS of 10 or more, and overall survival and progression-free survival in patients with oesophageal squamous cell carcinoma, PD-L1 CPS of 10 or more, and in all randomised patients regardless of histology, and had a manageable safety profile in the total as-treated population."""