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b22b5ab
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1 Parent(s): b3fa751

update app.py

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Files changed (1) hide show
  1. app.py +10 -8
app.py CHANGED
@@ -23,7 +23,7 @@ st.sidebar.write("""
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  3. If a dropdown menu pops up for a nigerian language, **select the target nigerian language.**
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  4. Click the Generate button to get a response below the text area.\n
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  **Note: Model's overall performance vary (hallucinates) due to model size and training data distribution (majorly from news articles and the bible). Performance may worsen significantly with other task outside text generation.
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- For other tasks, we suggest you try them several times.**\n
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  5. Lastly, you can play with some of the generation parameters below to improve performance.
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  """)
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@@ -128,13 +128,15 @@ async def generate_from_api(user_input, generation_config):
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  # Sample texts
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  sample_texts = {
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  "select":"",
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- "Tell me a story in pidgin": "Tell me a story in Yoruba",
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- "Oma Ede, Mi ji ogede...": "Oma Ede, Mi ji ogede mi a foroma orhorho edha meji ri eka. ",
 
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  "Igbo: N'ala Igbo ...": "N'ala Igbo, ọtụtụ ndị mmadụ kwenyere na e nwere mmiri ara na elu-ilu",
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- "who are you?": "who are you?",
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  "urhobo: Eshare nana ri...":"Eshare nana ri vwo ẹguọnọ rẹ iyono rẹ Aristotle vẹ Plato na",
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  "Efik: Ke eyo ...":"Ke eyo Jesus ye mme mbet esie, etop emi ama ada ifụre ọsọk mme Jew oro esịt okobụn̄ọde ke ntak idiọkido ke Israel, oro ẹkenyụn̄ ẹdude ke mfụhọ ke itie-ufụn mme nsunsu ido edinam Ido Ukpono Mme Jew eke akpa isua ikie.",
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- "Translate 'how are you?' to Yoruba": "Translate 'how are you?' to Yoruba",
 
 
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  "Classify the sentiment": "Anyi na-echefu oke ike.",
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  "what is the topic of this text": "Africa Free Trade Zone: Kò sí ìdènà láti kó ọjà láti orílẹ̀èdè kan sí òmíràn",
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  "diacritize this text: ": "E sun, Alaga, fun ise amalayi ti e n se ni Naijiria. E maa ba a lo, egbon!",
@@ -157,9 +159,9 @@ instruction_wrap = {
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  task_options = {
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  "select": "{}",
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  "Text Generation": "{}",
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- "Instruction Following": "<prompt> {} <response>:",
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  "Sentiment Classification": "<classify> {} <sentiment>:",
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  "Topic Classification": "<classify> {} <topic>",
 
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  "Title Generation": "<title> {} <headline>",
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  "Text Diacritization": "<diacritize> {}",
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  "Text Cleaning": "<clean> {}"
@@ -199,7 +201,7 @@ def wrap_text(text, task_value):
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200
 
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  # Text input
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- user_input = st.text_area("Enter text below **(PLEASE, FIRST READ THE INSTRUCTIONS ON HOW TO USE IN THE SIDE BAR FOR BETTER EXPERIENCE)**: ", sample_texts[sample_text])
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  user_input = instruction_wrap.get(sample_texts.get(user_input, user_input), user_input)
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  print("Final user input: ", user_input)
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  if st.button("Generate"):
@@ -238,7 +240,7 @@ if st.button("Generate"):
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  generated_text = "Neutral"
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240
  elif task == "Topic Classification":
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- generated_text = generated_text[:20]
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243
  full_output = st.empty()
244
 
 
23
  3. If a dropdown menu pops up for a nigerian language, **select the target nigerian language.**
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  4. Click the Generate button to get a response below the text area.\n
25
  **Note: Model's overall performance vary (hallucinates) due to model size and training data distribution (majorly from news articles and the bible). Performance may worsen significantly with other task outside text generation.
26
+ For other tasks, we suggest you try them several times due to the generator's sampling method.**\n
27
  5. Lastly, you can play with some of the generation parameters below to improve performance.
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  """)
29
 
 
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  # Sample texts
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  sample_texts = {
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  "select":"",
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+ "Hausa: Afirka tana da al'adu...": "Afirka tana da al'adu da harsuna masu yawa. Tana da albarkatu da wuraren yawon shakatawa masu ban mamaki.",
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+ "Yoruba: Ìmọ̀ sáyẹ́nsì àti...": "Ìmọ̀ sáyẹ́nsì àti tẹ̀knọ́lójì ń ṣe émi lóore níye lori Áfíríkà. Ó ń fún àwọn ènìyàn ní ànfààní láti dá irọyin àti kí wọ́n lè ṣe àwọn nǹkan tuntun.",
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+ "Efik: Oma Ede, Mi ji ogede...": "Oma Ede, Mi ji ogede mi a foroma orhorho edha meji ri eka. ",
134
  "Igbo: N'ala Igbo ...": "N'ala Igbo, ọtụtụ ndị mmadụ kwenyere na e nwere mmiri ara na elu-ilu",
 
135
  "urhobo: Eshare nana ri...":"Eshare nana ri vwo ẹguọnọ rẹ iyono rẹ Aristotle vẹ Plato na",
136
  "Efik: Ke eyo ...":"Ke eyo Jesus ye mme mbet esie, etop emi ama ada ifụre ọsọk mme Jew oro esịt okobụn̄ọde ke ntak idiọkido ke Israel, oro ẹkenyụn̄ ẹdude ke mfụhọ ke itie-ufụn mme nsunsu ido edinam Ido Ukpono Mme Jew eke akpa isua ikie.",
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+ "Tell me a story in pidgin": "Tell me a story Pidgin",
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+ "who are you?": "who are you?",
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+ # "Translate 'how are you?' to Yoruba": "Translate 'how are you?' to Yoruba",
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  "Classify the sentiment": "Anyi na-echefu oke ike.",
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  "what is the topic of this text": "Africa Free Trade Zone: Kò sí ìdènà láti kó ọjà láti orílẹ̀èdè kan sí òmíràn",
142
  "diacritize this text: ": "E sun, Alaga, fun ise amalayi ti e n se ni Naijiria. E maa ba a lo, egbon!",
 
159
  task_options = {
160
  "select": "{}",
161
  "Text Generation": "{}",
 
162
  "Sentiment Classification": "<classify> {} <sentiment>:",
163
  "Topic Classification": "<classify> {} <topic>",
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+ "Instruction Following" : "<prompt> {} <response>:",
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  "Title Generation": "<title> {} <headline>",
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  "Text Diacritization": "<diacritize> {}",
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  "Text Cleaning": "<clean> {}"
 
201
 
202
 
203
  # Text input
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+ user_input = st.text_area("Enter text below **(PLEASE, FIRST READ ALL INSTRUCTIONS IN THE SIDEBAR FOR A BETTER EXPERIENCE)**: ", sample_texts[sample_text])
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  user_input = instruction_wrap.get(sample_texts.get(user_input, user_input), user_input)
206
  print("Final user input: ", user_input)
207
  if st.button("Generate"):
 
240
  generated_text = "Neutral"
241
 
242
  elif task == "Topic Classification":
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+ generated_text = generated_text.split(" ")[0][:20]
244
 
245
  full_output = st.empty()
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