Update classifier.py

classifier.py

@@ -7,16 +7,16 @@ def classify(tweet, event_model, hftoken, threshold):
     results = {"text": None,  "event": None, "score": None}
     
     # event type prediction with transformers pipeline
-    # event_predictor = tpipeline(task="text-classification", model=event_model, 
-    #                            batch_size=512, token=hftoken, device="cpu")
-    # tokenizer_kwargs = {'padding': True, 'truncation': True, 'max_length': 512}
-    # prediction = event_predictor(tweet, **tokenizer_kwargs)[0]
+    event_predictor = tpipeline(task="text-classification", model=event_model, 
+                               batch_size=512, token=hftoken, device="cpu")
+    tokenizer_kwargs = {'padding': True, 'truncation': True, 'max_length': 512}
+    prediction = event_predictor(tweet, **tokenizer_kwargs)[0]
 
 
     # with onnx pipeline 
-    onnx_classifier = opipeline("text-classification", model=event_model, accelerator="ort", 
-                                batch_size=512, token=hftoken, device="cpu")
-    prediction = onnx_classifier(tweet)[0]
+    # onnx_classifier = opipeline("text-classification", model=event_model, accelerator="ort", 
+    #                             batch_size=512, token=hftoken, device="cpu")
+    # prediction = onnx_classifier(tweet)[0]
     
     
     results["text"] = tweet