mlkorra commited on
Commit
3f6b043
1 Parent(s): 33ae6dd

app update

Browse files
Files changed (1) hide show
  1. app.py +15 -13
app.py CHANGED
@@ -6,6 +6,8 @@ from transformers import pipeline
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  import os
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  import json
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  import random
 
 
9
 
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  @st.cache(show_spinner=False,persist=True)
11
  def load_model(masked_text,model_name):
@@ -19,7 +21,7 @@ def load_model(masked_text,model_name):
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  masked_text = masked_text.replace("<mask>",MASK_TOKEN)
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  result_sentence = nlp(masked_text)
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- return result_sentence[0]['sequence']
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  def main():
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@@ -30,7 +32,7 @@ def main():
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31
  models = st.multiselect(
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  "Choose models",
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- ['flax-community/roberta-hindi','mrm8488/HindiBERTa','ai4bharat/indic-bert',\
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  'neuralspace-reverie/indic-transformers-hi-bert',
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  'surajp/RoBERTa-hindi-guj-san'],
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  ["flax-community/roberta-hindi"]
@@ -44,14 +46,12 @@ def main():
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  st.sidebar.title("Hindi MLM")
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  pick_random = st.sidebar.checkbox("Pick any random text")
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-
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- #st.write('You selected:', masked_text)
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- results_df = pd.DataFrame(columns = ['Model Name','Masked Text','Filled Masked Text'])
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  model_names = []
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- masked_texts = []
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  filled_masked_texts = []
 
55
 
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  if pick_random:
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  random_text = texts[random.randint(0,texts.shape[0]-1)]
@@ -60,22 +60,24 @@ def main():
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  select_text = st.sidebar.selectbox('Select any of the following text',\
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  texts)
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  masked_text = st.text_area("Please type a masked sentence to fill",select_text)
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-
 
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  if st.button('Fill the Mask!'):
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  with st.spinner("Filling the Mask..."):
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  for selected_model in models:
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- filled_sentence = load_model(masked_text,selected_model)
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  model_names.append(selected_model)
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- masked_texts.append(masked_text)
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  filled_masked_texts.append(filled_sentence)
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  results_df['Model Name'] = model_names
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- results_df['Masked Text'] = masked_texts
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- results_df['Filled Masked Text'] = filled_masked_texts
 
 
 
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- st.table(results_df)
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-
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  if __name__ == "__main__":
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  main()
6
  import os
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  import json
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  import random
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+ import numpy as np
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+
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12
  @st.cache(show_spinner=False,persist=True)
13
  def load_model(masked_text,model_name):
21
  masked_text = masked_text.replace("<mask>",MASK_TOKEN)
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  result_sentence = nlp(masked_text)
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+ return result_sentence[0]['sequence'], result_sentence[0]['token_str']
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26
  def main():
27
 
32
 
33
  models = st.multiselect(
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  "Choose models",
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+ ['flax-community/roberta-hindi','mrm8488/HindiBERTa',\
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  'neuralspace-reverie/indic-transformers-hi-bert',
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  'surajp/RoBERTa-hindi-guj-san'],
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  ["flax-community/roberta-hindi"]
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  st.sidebar.title("Hindi MLM")
47
 
48
  pick_random = st.sidebar.checkbox("Pick any random text")
 
 
49
 
50
+ results_df = pd.DataFrame(columns = ['Model Name','Filled Token','Filled Text'])
51
 
52
  model_names = []
 
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  filled_masked_texts = []
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+ filled_tokens = []
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56
  if pick_random:
57
  random_text = texts[random.randint(0,texts.shape[0]-1)]
60
  select_text = st.sidebar.selectbox('Select any of the following text',\
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  texts)
62
  masked_text = st.text_area("Please type a masked sentence to fill",select_text)
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+
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+ #pd.set_option('max_colwidth',30)
65
  if st.button('Fill the Mask!'):
66
  with st.spinner("Filling the Mask..."):
67
 
68
  for selected_model in models:
69
 
70
+ filled_sentence,filled_token = load_model(masked_text,selected_model)
71
  model_names.append(selected_model)
72
+ filled_tokens.append(filled_token)
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  filled_masked_texts.append(filled_sentence)
74
 
75
  results_df['Model Name'] = model_names
76
+ results_df['Filled Token'] = filled_tokens
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+ results_df['Filled Text'] = filled_masked_texts
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+
79
+ #st.table(results_df)
80
+ st.write(results_df)
81
 
 
 
82
  if __name__ == "__main__":
83
  main()