Update pipeline.py

pipeline.py

@@ -15,6 +15,10 @@ class PreTrainedPipeline():
         nltk.download('punkt')
         self.model = AutoModelForSeq2SeqLM.from_pretrained(path)
         self.tokenizer = AutoTokenizer.from_pretrained(path)
+        print("Loading pipe")
+        self.pipe = pipeline("text-classification", model="p-christ/QandAClassifier")
+        print("Pipe loaded")        
+
         
         self.model_type="t5"
         # self.device = "cuda" if torch.cuda.is_available() else "cpu"