change chkpt path

sentiment.py

@@ -3,7 +3,8 @@ from transformers import AutoModelForSequenceClassification,AutoTokenizer
 
 chkpt='distilbert-base-uncased-finetuned-sst-2-english'
 model=AutoModelForSequenceClassification.from_pretrained(chkpt)
-tokenizer=AutoTokenizer.from_pretrained('sentiment_classifier/')
+tokenizer=AutoTokenizer.from_pretrained(chkpt)
+# tokenizer=AutoTokenizer.from_pretrained('sentiment_classifier/')
 
 def classify_sentiment(texts,model=model,tokenizer=tokenizer):
     """

sentiment_onnx.py

@@ -12,7 +12,8 @@ python3 -m transformers.onnx --model= distilbert-base-uncased-finetuned-sst-2-en
 """
 chkpt='distilbert-base-uncased-finetuned-sst-2-english'
 model= AutoModelForSequenceClassification.from_pretrained(chkpt)
-tokenizer= AutoTokenizer.from_pretrained('sentiment_classifier/')
+tokenizer= AutoTokenizer.from_pretrained('chkpt')
+# tokenizer= AutoTokenizer.from_pretrained('sentiment_classifier/')
 
 """ 
 or download the model directly from hub --

sentiment_onnx_classify.py

@@ -3,15 +3,17 @@ import torch
 from transformers import AutoTokenizer
 import numpy as np
 
-tokenizer=AutoTokenizer.from_pretrained("sentiment_classifier/")
+chkpt='distilbert-base-uncased-finetuned-sst-2-english'
+tokenizer=AutoTokenizer.from_pretrained(chkpt)
+# tokenizer=AutoTokenizer.from_pretrained("sentiment_classifier/")
 
 #create onnx & onnx_int_8 sessions
 session=ort.InferenceSession("sent_clf_onnx/sentiment_classifier_onnx.onnx")
 session_int8=ort.InferenceSession("sent_clf_onnx/sentiment_classifier_onnx_int8.onnx")
 
-options=ort.SessionOptions()
-options.inter_op_num_threads=1
-options.intra_op_num_threads=1
+# options=ort.SessionOptions()
+# options.inter_op_num_threads=1
+# options.intra_op_num_threads=1
 
 def classify_sentiment_onnx(texts,_model=session,_tokenizer=tokenizer):
     """