hassiahk commited on
Commit
76d5628
1 Parent(s): 3c075e2

Added models info

Browse files

Files changed (4) hide show
  1. app.py +2 -3
  2. apps/about.py +4 -2
  3. apps/{inference.py → mlm.py} +16 -16
  4. multiapp.py +1 -4
app.py CHANGED
@@ -1,11 +1,10 @@
1
- import streamlit as st
2
  from multiapp import MultiApp
3
- from apps import about, inference
4
 
5
 
6
  def main():
7
  app = MultiApp()
8
- app.add_app("Inference", inference.app)
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  app.add_app("About", about.app)
10
  app.run()
11
 
1
+ from apps import about, mlm
2
  from multiapp import MultiApp
 
3
 
4
 
5
  def main():
6
  app = MultiApp()
7
+ app.add_app("Fill Mask", mlm.app)
8
  app.add_app("About", about.app)
9
  app.run()
10
 
apps/about.py CHANGED
@@ -1,6 +1,8 @@
1
- import streamlit as st
2
- import os
3
  import json
 
 
 
 
4
 
5
  def read_markdown(path, folder="./About/"):
6
  with open(os.path.join(folder, path)) as f:
 
 
1
  import json
2
+ import os
3
+
4
+ import streamlit as st
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+
6
 
7
  def read_markdown(path, folder="./About/"):
8
  with open(os.path.join(folder, path)) as f:
apps/{inference.py → mlm.py} RENAMED
@@ -1,12 +1,11 @@
1
- from pandas.io.formats.format import return_docstring
2
- import streamlit as st
3
- import pandas as pd
4
- from transformers import AutoTokenizer, AutoModelForMaskedLM
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- from transformers import pipeline
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- import os
7
  import json
 
8
  import random
9
 
 
 
 
 
10
  with open("config.json") as f:
11
  cfg = json.loads(f.read())
12
 
@@ -27,13 +26,8 @@ def load_model(masked_text, model_name):
27
 
28
 
29
  def app():
30
- st.markdown(
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- "<h1 style='text-align: center; color: green;'>RoBERTa Hindi</h1>",
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- unsafe_allow_html=True,
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- )
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- st.markdown(
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- "This demo uses multiple hindi transformer models for Masked Language Modelling (MLM)."
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- )
37
 
38
  models_list = list(cfg["models"].keys())
39
 
@@ -50,6 +44,14 @@ def app():
50
 
51
  results_df = pd.DataFrame(columns=["Model Name", "Filled Token", "Filled Text"])
52
 
 
 
 
 
 
 
 
 
53
  model_names = []
54
  filled_masked_texts = []
55
  filled_tokens = []
@@ -67,9 +69,7 @@ def app():
67
 
68
  for selected_model in models:
69
 
70
- filled_sentence, filled_token = load_model(
71
- masked_text, cfg["models"][selected_model]
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- )
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  model_names.append(selected_model)
74
  filled_tokens.append(filled_token)
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  filled_masked_texts.append(filled_sentence)
 
 
 
 
 
 
1
  import json
2
+ import os
3
  import random
4
 
5
+ import pandas as pd
6
+ import streamlit as st
7
+ from transformers import AutoModelForMaskedLM, AutoTokenizer, pipeline
8
+
9
  with open("config.json") as f:
10
  cfg = json.loads(f.read())
11
 
26
 
27
 
28
  def app():
29
+ st.header("RoBERTa Hindi")
30
+ st.markdown("This demo uses multiple hindi transformer models for Masked Language Modelling (MLM).")
 
 
 
 
 
31
 
32
  models_list = list(cfg["models"].keys())
33
 
44
 
45
  results_df = pd.DataFrame(columns=["Model Name", "Filled Token", "Filled Text"])
46
 
47
+ st.sidebar.markdown(
48
+ "Models\n"
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+ "- [RoBERTa Hindi](https://huggingface.co/flax-community/roberta-hindi)\n"
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+ "- [Indic Transformers Hindi](https://huggingface.co/neuralspace-reverie/indic-transformers-hi-bert)\n"
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+ "- [HindiBERTa]((https://huggingface.co/mrm8488/HindiBERTa)\n"
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+ "- [RoBERTa Hindi Guj San](https://huggingface.co/surajp/RoBERTa-hindi-guj-san)"
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+ )
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+
55
  model_names = []
56
  filled_masked_texts = []
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  filled_tokens = []
69
 
70
  for selected_model in models:
71
 
72
+ filled_sentence, filled_token = load_model(masked_text, cfg["models"][selected_model])
 
 
73
  model_names.append(selected_model)
74
  filled_tokens.append(filled_token)
75
  filled_masked_texts.append(filled_sentence)
multiapp.py CHANGED
@@ -1,5 +1,3 @@
1
- """Frameworks for running multiple Streamlit applications as a single app.
2
- """
3
  import streamlit as st
4
 
5
 
@@ -12,7 +10,6 @@ class MultiApp:
12
 
13
  def run(self):
14
  st.sidebar.header("Navigation")
15
- app = st.sidebar.selectbox("", self.apps, format_func=lambda app: app["title"])
16
 
17
  app["function"]()
18
-
 
 
1
  import streamlit as st
2
 
3
 
10
 
11
  def run(self):
12
  st.sidebar.header("Navigation")
13
+ app = st.sidebar.radio("", self.apps, format_func=lambda app: app["title"])
14
 
15
  app["function"]()