Hafizhzpa commited on
Commit
23e9146
·
verified ·
1 Parent(s): 2193f37

Update app.py

Browse files

solve bug run not found

Files changed (1) hide show
  1. app.py +9 -3
app.py CHANGED
@@ -10,11 +10,11 @@ classifier = ZeroShotClassificationPipeline(model=model, tokenizer=tokenizer,ypo
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  st.markdown("<h2 style='text-align: center; color: black;'>NLP Project </h2>", unsafe_allow_html=True)
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  st.markdown("<p style='text-align: center; color: black;'>Hafizh Zaki Prasetyo Adi|[email protected]|https://www.linkedin.com/in/hafizhzpa/ </p>", unsafe_allow_html=True)
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  part=st.sidebar.radio("project",["sentimen", "emosi", "label khusus"],captions = ["menentukan label sentimen", "menentukan label emosi", "klasifikasi berdasarkan label yang ditentukan"])
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- col1, col2 = st.columns(2)
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- text = col1.text_area('text', 'Saya sudah menggunakan produk ini selama sebulan dan saya sangat puas dengan hasilnya')
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- multiclass = col1.checkbox('Izinkan multi label')
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  if part=='label khusus':
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  start=time.time()
 
 
 
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  label = col1.text_area('label', 'positive,negative,neutral')
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  if col1.button('run'):
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  candidate_labels = label.split(',')
@@ -32,6 +32,9 @@ if part=='label khusus':
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  col2.text(str(round(result['scores'][0]*100,2))+"%")
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  if part=='sentimen':
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  start=time.time()
 
 
 
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  if col1.button('run'):
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  candidate_labels = ['positive','negative','neutral']
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  result=classifier(text, candidate_labels, multi_label=multiclass)
@@ -48,6 +51,9 @@ if part=='sentimen':
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  col2.text(str(round(result['scores'][0]*100,2))+"%")
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  if part=='emotion':
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  start=time.time()
 
 
 
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  if col1.button('run'):
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  candidate_labels = ["bahagia", "sedih", "takut", "marah", "antisipasi", "terkejut", "jijik","percaya"]
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  result=classifier(text, candidate_labels, multi_label=multiclass)
 
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  st.markdown("<h2 style='text-align: center; color: black;'>NLP Project </h2>", unsafe_allow_html=True)
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  st.markdown("<p style='text-align: center; color: black;'>Hafizh Zaki Prasetyo Adi|[email protected]|https://www.linkedin.com/in/hafizhzpa/ </p>", unsafe_allow_html=True)
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  part=st.sidebar.radio("project",["sentimen", "emosi", "label khusus"],captions = ["menentukan label sentimen", "menentukan label emosi", "klasifikasi berdasarkan label yang ditentukan"])
 
 
 
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  if part=='label khusus':
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  start=time.time()
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+ col1, col2 = st.columns(2)
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+ text = col1.text_area('text', 'Saya sudah menggunakan produk ini selama sebulan dan saya sangat puas dengan hasilnya')
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+ multiclass = col1.checkbox('Izinkan multi label')
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  label = col1.text_area('label', 'positive,negative,neutral')
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  if col1.button('run'):
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  candidate_labels = label.split(',')
 
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  col2.text(str(round(result['scores'][0]*100,2))+"%")
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  if part=='sentimen':
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  start=time.time()
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+ col1, col2 = st.columns(2)
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+ text = col1.text_area('text', 'Saya sudah menggunakan produk ini selama sebulan dan saya sangat puas dengan hasilnya')
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+ multiclass = col1.checkbox('Izinkan multi label')
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  if col1.button('run'):
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  candidate_labels = ['positive','negative','neutral']
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  result=classifier(text, candidate_labels, multi_label=multiclass)
 
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  col2.text(str(round(result['scores'][0]*100,2))+"%")
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  if part=='emotion':
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  start=time.time()
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+ col1, col2 = st.columns(2)
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+ text = col1.text_area('text', 'Saya sudah menggunakan produk ini selama sebulan dan saya sangat puas dengan hasilnya')
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+ multiclass = col1.checkbox('Izinkan multi label')
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  if col1.button('run'):
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  candidate_labels = ["bahagia", "sedih", "takut", "marah", "antisipasi", "terkejut", "jijik","percaya"]
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  result=classifier(text, candidate_labels, multi_label=multiclass)