To use the model, add the following from the transformers package: 

(1) ClinicalBERT tokenizer: 


tokenizer = AutoTokenizer.from_pretrained("emilyalsentzer/Bio_ClinicalBERT")

(2) Model type:

model = BertForSequenceClassification.from_pretrained(checkpoint_directory, num_labels=3)

{}
transformers pytorch bert text-classification autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #autotrain_compatible #endpoints_compatible #region-us 

To use the model, add the following from the transformers package: 

(1) ClinicalBERT tokenizer: 


tokenizer = AutoTokenizer.from_pretrained("emilyalsentzer/Bio_ClinicalBERT")

(2) Model type:

model = BertForSequenceClassification.from_pretrained(checkpoint_directory, num_labels=3)

TAGS
#transformers #pytorch #bert #text-classification #autotrain_compatible #endpoints_compatible #region-us 
