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Runtime error
Runtime error
Jeffrey Rathgeber Jr
commited on
testprint
Browse files
app.py
CHANGED
@@ -71,39 +71,39 @@ if option == 'MILESTONE 3: FINE-TUNED':
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st.write('TESTING1')
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model_name_0 = "Rathgeberj/milestone3_0"
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model_0 = AutoModelForSequenceClassification.from_pretrained(model_name_0)
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tokenizer_0 = AutoTokenizer.from_pretrained(model_name_0)
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classifier_0 = pipeline(task="sentiment-analysis", model=model_0, tokenizer=tokenizer_0)
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model_name_1 = "Rathgeberj/milestone3_1"
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model_1 = AutoModelForSequenceClassification.from_pretrained(model_name_1)
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tokenizer_1 = AutoTokenizer.from_pretrained(model_name_1)
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classifier_1 = pipeline(task="sentiment-analysis", model=model_1, tokenizer=tokenizer_1)
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model_name_2 = "Rathgeberj/milestone3_2"
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model_2 = AutoModelForSequenceClassification.from_pretrained(model_name_2)
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tokenizer_2 = AutoTokenizer.from_pretrained(model_name_2)
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classifier_2 = pipeline(task="sentiment-analysis", model=model_2, tokenizer=tokenizer_2)
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model_name_3 = "Rathgeberj/milestone3_3"
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model_3 = AutoModelForSequenceClassification.from_pretrained(model_name_3)
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tokenizer_3 = AutoTokenizer.from_pretrained(model_name_3)
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classifier_3 = pipeline(task="sentiment-analysis", model=model_3, tokenizer=tokenizer_3)
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model_name_4 = "Rathgeberj/milestone3_4"
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model_4 = AutoModelForSequenceClassification.from_pretrained(model_name_4)
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tokenizer_4 = AutoTokenizer.from_pretrained(model_name_4)
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classifier_4 = pipeline(task="sentiment-analysis", model=model_4, tokenizer=tokenizer_4)
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model_name_5 = "Rathgeberj/milestone3_5"
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model_5 = AutoModelForSequenceClassification.from_pretrained(model_name_5)
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tokenizer_5 = AutoTokenizer.from_pretrained(model_name_5)
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classifier_5 = pipeline(task="sentiment-analysis", model=model_5, tokenizer=tokenizer_5)
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models = [model_0, model_1, model_2, model_3, model_4, model_5]
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tokenizers = [tokenizer_0, tokenizer_1, tokenizer_2, tokenizer_3, tokenizer_4, tokenizer_5]
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classifiers = [classifier_0, classifier_1, classifier_2, classifier_3, classifier_4, classifier_5]
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st.write('TESTING2')
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st.write('TESTING1')
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# model_name_0 = "Rathgeberj/milestone3_0"
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# model_0 = AutoModelForSequenceClassification.from_pretrained(model_name_0)
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# tokenizer_0 = AutoTokenizer.from_pretrained(model_name_0)
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# classifier_0 = pipeline(task="sentiment-analysis", model=model_0, tokenizer=tokenizer_0)
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# model_name_1 = "Rathgeberj/milestone3_1"
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# model_1 = AutoModelForSequenceClassification.from_pretrained(model_name_1)
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# tokenizer_1 = AutoTokenizer.from_pretrained(model_name_1)
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# classifier_1 = pipeline(task="sentiment-analysis", model=model_1, tokenizer=tokenizer_1)
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# model_name_2 = "Rathgeberj/milestone3_2"
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# model_2 = AutoModelForSequenceClassification.from_pretrained(model_name_2)
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# tokenizer_2 = AutoTokenizer.from_pretrained(model_name_2)
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# classifier_2 = pipeline(task="sentiment-analysis", model=model_2, tokenizer=tokenizer_2)
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# model_name_3 = "Rathgeberj/milestone3_3"
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# model_3 = AutoModelForSequenceClassification.from_pretrained(model_name_3)
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# tokenizer_3 = AutoTokenizer.from_pretrained(model_name_3)
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# classifier_3 = pipeline(task="sentiment-analysis", model=model_3, tokenizer=tokenizer_3)
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# model_name_4 = "Rathgeberj/milestone3_4"
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# model_4 = AutoModelForSequenceClassification.from_pretrained(model_name_4)
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# tokenizer_4 = AutoTokenizer.from_pretrained(model_name_4)
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# classifier_4 = pipeline(task="sentiment-analysis", model=model_4, tokenizer=tokenizer_4)
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# model_name_5 = "Rathgeberj/milestone3_5"
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# model_5 = AutoModelForSequenceClassification.from_pretrained(model_name_5)
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# tokenizer_5 = AutoTokenizer.from_pretrained(model_name_5)
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# classifier_5 = pipeline(task="sentiment-analysis", model=model_5, tokenizer=tokenizer_5)
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# models = [model_0, model_1, model_2, model_3, model_4, model_5]
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# tokenizers = [tokenizer_0, tokenizer_1, tokenizer_2, tokenizer_3, tokenizer_4, tokenizer_5]
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# classifiers = [classifier_0, classifier_1, classifier_2, classifier_3, classifier_4, classifier_5]
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# st.write('TESTING2')
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