ZephyruSalsify commited on
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2c5eccf
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1 Parent(s): be51d5d

Update app.py

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Files changed (1) hide show
  1. app.py +1 -19
app.py CHANGED
@@ -5,7 +5,7 @@ access = "hf_"
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  token = "hhbFNpjKohezoexWMlyPUpvJQLWlaFhJaa"
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  # Load the text classification model pipeline
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- analysis = pipeline("text-classification", model='ZephyruSalsify/FinNews_SentimentAnalysis_Test')
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  classification = pipeline("text-classification", model="nickmuchi/finbert-tone-finetuned-finance-topic-classification", token=access+token)
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  st.set_page_config(page_title="Financial News Analysis", page_icon="♕")
@@ -24,24 +24,6 @@ if st.button("Analyze"):
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  # Perform text analysis on the input text
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  results_1 = analysis(text)[0]
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  results_2 = classification(text)[0]
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-
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- # Display the analysis result
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- #max_score_1 = float('-inf')
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- #max_label_1 = ''
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-
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- #for result_1 in results_1:
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- # if result_1['score'] > max_score_1:
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- # max_score_1 = result_1['score']
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- # max_label_1 = result_1['label']
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-
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- # Display the classification result
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- #max_score_2 = float('-inf')
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- #max_label_2 = ''
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-
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- #for result_2 in results_2:
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- # if result_2['score'] > max_score_2:
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- # max_score_2 = result_2['score']
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- # max_label_2 = result_2['label']
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  st.write("Financial Text:", text)
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  st.write("Trend:", results_1["label"])
 
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  token = "hhbFNpjKohezoexWMlyPUpvJQLWlaFhJaa"
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  # Load the text classification model pipeline
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+ analysis = pipeline("text-classification", model='ZephyruSalsify/FinNews_SentimentAnalysis')
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  classification = pipeline("text-classification", model="nickmuchi/finbert-tone-finetuned-finance-topic-classification", token=access+token)
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  st.set_page_config(page_title="Financial News Analysis", page_icon="♕")
 
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  # Perform text analysis on the input text
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  results_1 = analysis(text)[0]
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  results_2 = classification(text)[0]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  st.write("Financial Text:", text)
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  st.write("Trend:", results_1["label"])