Update app.py

app.py

@@ -48,17 +48,17 @@ st.sidebar.write("""
    - Don't select a sample text if using your own text.
 
 4. **Select Nigerian Language:**
-   - If prompted, choose the Nigerian language (base for diacritization/cleaning, target for translation).
+   - If prompted, choose the Nigerian language (it represents the input/base language for diacritization/cleaning, target language for translation).
 
 5. **Generate Output:**
    - Click the Generate button.
 
 6. **Translation Tips:**
-   - English as the target language gives the best results. English as the base language performs poorly.
+   - English as the target language gives the best results.
 
 7. **Performance Note:**
    - The model's performance varies due to its size and training data. It performs best on text generation and translation.
-   - For other tasks, try multiple times due to sampling.
+   - For other tasks, try multiple times due to the generator's sampling parameter settings.
 
 8. **Adjust Parameters:**
    - Experiment with the generation parameters to improve performance.
@@ -99,9 +99,9 @@ generation_config = {
 # Streamlit app
 st.title("SabiYarn-125M : Generates text in multiple Nigerian languages.")
 
-st.write("**Supported Languages: English, Yoruba, Igbo, Hausa, Pidgin, Efik, Urhobo, Fulfulde, Fulah. \nResults might not be coherent for less represented languages (i.e Efik, \
+st.write("**Supported Languages: English, Yoruba, Igbo, Hausa, Pidgin, Efik, Urhobo, Fulfulde, Fulah. \nResults may not be coherent for less represented languages (i.e Efik, \
 Urhobo, Fulfulde, Fulah).**")
-st.write("**It might take a while (~25s) to return an output on the first 'generate' click.**")
+st.write("**It may take a while (~25s) to return an output on the first 'generate' click.**")
 st.write("**For convenience, you can use chatgpt to copy text and evaluate model output.**")
 st.write("-" * 50)
 
@@ -214,7 +214,6 @@ def wrap_text(text, task_value):
         return text
     return task_value.format(text)
 
-
 # Text input 
 user_input = st.text_area("Enter text below **(PLEASE, FIRST READ ALL INSTRUCTIONS IN THE SIDEBAR CAREFULLY FOR THE BEST EXPERIENCE)**: ", sample_texts[sample_text])
 user_input = instruction_wrap.get(sample_texts.get(user_input, user_input), user_input)