Update app.py

app.py

@@ -13,19 +13,19 @@ model_asr = Wav2Vec2ForCTC.from_pretrained(model_name)
 model_name = 'qanastek/XLMRoberta-Alexa-Intents-Classification'
 tokenizer_intent = AutoTokenizer.from_pretrained(model_name)
 model_intent = AutoModelForSequenceClassification.from_pretrained(model_name)
-classifier_intent = TextClassificationPipeline(model=model_intent, tokenizer=tokenizer_intent, device=0)
+classifier_intent = TextClassificationPipeline(model=model_intent, tokenizer=tokenizer_intent)
 
 # Classifier Language
 model_name = 'qanastek/51-languages-classifier'
 tokenizer_langs = AutoTokenizer.from_pretrained(model_name)
 model_langs = AutoModelForSequenceClassification.from_pretrained(model_name)
-classifier_language = TextClassificationPipeline(model=model_langs, tokenizer=tokenizer_langs, device=0)
+classifier_language = TextClassificationPipeline(model=model_langs, tokenizer=tokenizer_langs)
 
 # NER Extractor
 model_name = 'qanastek/XLMRoberta-Alexa-Intents-NER-NLU'
 tokenizer_ner = AutoTokenizer.from_pretrained(model_name)
 model_ner = AutoModelForTokenClassification.from_pretrained(model_name)
-predict_ner = TokenClassificationPipeline(model=model_ner, tokenizer=tokenizer_ner, device=0)
+predict_ner = TokenClassificationPipeline(model=model_ner, tokenizer=tokenizer_ner)
 
 def greet(name):
     return "Hello " + name + "!!"