Update classifier.py

classifier.py

@@ -1,16 +1,22 @@
 import spaces
-from transformers import pipeline
+from transformers import pipeline as tpipeline
+from optimum.pipelines import pipeline as opipline
 
 #@spaces.GPU(duration=60)
 def classify(tweet, event_model, hftoken, threshold):
+    results = {"text": None,  "event": None, "score": None}
     
-    # event type prediction
-    event_predictor = pipeline(task="text-classification", model=event_model, 
-                               batch_size=512, token=hftoken, device="cpu")
-    tokenizer_kwargs = {'padding': True, 'truncation': True, 'max_length': 512}
+    # event type prediction with transformers pipeline
+    # event_predictor = pipeline(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]
 
-    results = {"text": None,  "event": None, "score": None}
-    prediction = event_predictor(tweet, **tokenizer_kwargs)[0]
+
+    # with onnx pipeline 
+    onnx_classifier = pipeline("text-classification", model=event_model, accelerator="ort")
+    prediction = onnx_classifier(text)[0]
+    
     
     results["text"] = tweet