Update app.py

app.py

@@ -18,10 +18,10 @@ sentiment_model = pipeline("text-classification", model="AhmedTaha012/managersFe
 increase_decrease_model = pipeline("text-classification", model="AhmedTaha012/nextQuarter-status-V1.1.9")
 tokenizerTopic = AutoTokenizer.from_pretrained("nickmuchi/finbert-tone-finetuned-finance-topic-classification",use_fast=True,token="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")
 modelTopic = AutoModelForSequenceClassification.from_pretrained("nickmuchi/finbert-tone-finetuned-finance-topic-classification",token="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")
-# torch.compile(modelTopic)
+torch.compile(modelTopic)
 tokenizer = AutoTokenizer.from_pretrained("AhmedTaha012/finance-ner-v0.0.9-finetuned-ner")
 model = AutoModelForTokenClassification.from_pretrained("AhmedTaha012/finance-ner-v0.0.9-finetuned-ner")
-# torch.compile(model)
+torch.compile(model)
 # torch.compile(model)
 nlpPipe = pipeline("ner", model=model, tokenizer=tokenizer, grouped_entities=True)
 def getSpeakers(data):