Update classifier.py

classifier.py

@@ -1,17 +1,13 @@
 import spaces
-from transformers import AutoTokenizer, pipeline
+from transformers import tpipeline as tpipeline
 # from optimum.pipelines import pipeline as opipeline
-from optimum.onnxruntime import ORTModelForSequenceClassification
 
 #@spaces.GPU(duration=60)
 def classify(tweet, event_model, hftoken, threshold):
     results = {"text": None,  "event": None, "score": None}
-
-    model = ORTModelForSequenceClassification.from_pretrained(event_model)
-    tokenizer = AutoTokenizer.from_pretrained(event_model)
     
     # event type prediction with transformers pipeline
-    event_predictor = pipeline(task="text-classification", model=model, tokenizer=tokenizer,  #model=event_model
+    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]