Update app.py

app.py

@@ -16,16 +16,44 @@ model = AutoModelForCausalLM.from_pretrained(repo_name, trust_remote_code=True).
 
 # Add sidebar with instructions
 st.sidebar.title("Instructions: How to use")
+# st.sidebar.write("""
+# 1. Write something in the text area (a prompt or random text) or use the dropdown menu to select predefined sample text.
+# 2. Select a task from the **task dropdown menu** below only if you are providing your own text. **This is very important as it ensures the model responds accordingly.**
+# 3. If you are providing your own text, please do not select any predefined sample text from the dropdown menu.
+# 3. If a dropdown menu pops up for a nigerian language, **select the nigerian language (base language for diacritization and text cleaning tasks, target language for translation task).**
+# 4. Then, click the Generate button.\n
+# 5. For Translation tasks, setting english as the target language yields the best result (english as base language performs the worst).
+# **Note: Model's overall performance vary (hallucinates) due to model size and training data distribution (majorly from articles and the bible). Performance may worsen with other task outside text generation and translation.
+# For other tasks, we suggest you try them several times due to the generator's sampling method.**\n
+# 6. Lastly, you can play with some of the generation parameters below to improve performance.
+# """)
+
 st.sidebar.write("""
-1. Write something in the text area (a prompt or random text) or use the dropdown menu to select predefined sample text.
-2. Select a task from the **task dropdown menu** below only if you are providing your own text. **This is very important as it ensures the model responds accordingly.**
-3. If you are providing your own text, please do not select any predefined sample text from the dropdown menu.
-3. If a dropdown menu pops up for a nigerian language, **select the nigerian language (base language for diacritization and text cleaning tasks, target language for translation task).**
-4. Then, click the Generate button.\n
-5. For Translation tasks, setting english as the target language yields the best result (english as base language performs the worst).
-**Note: Model's overall performance vary (hallucinates) due to model size and training data distribution (majorly from articles and the bible). Performance may worsen with other task outside text generation and translation.
-For other tasks, we suggest you try them several times due to the generator's sampling method.**\n
-6. Lastly, you can play with some of the generation parameters below to improve performance.
+1. **Write Text or Select Sample:**
+   - Enter text in the text area or use the dropdown to choose a sample.
+
+2. **Select a Task:**
+   - Choose a task from the **task dropdown** if using your own text.
+   - **Important:** This ensures correct model response.
+
+3. **Avoid Conflicts:**
+   - 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).
+
+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.
+
+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.
+
+8. **Adjust Parameters:**
+   - Experiment with the generation parameters to improve performance.
 """)
 
 max_length = 100 
@@ -48,17 +76,6 @@ repetition_penalty = st.sidebar.slider("Repetition Penalty: Discourages token re
 length_penalty = st.sidebar.slider("Length Penalty: Discourages poor output as token length grows.", min_value=0.1, max_value=10.0, value=length_penalty)
 
 
-# Define generation configuration
-# max_length = st.sidebar.slider("Max Length", min_value=10, max_value=500, value=100)
-# max_new_tokens = st.sidebar.slider("Max tokens", min_value=30, max_value=768, value=50)
-# num_beams = st.sidebar.slider("Number of Beams", min_value=1, max_value=10, value=5)
-# temperature = st.sidebar.slider("Temperature", min_value=0.1, max_value=2.0, value=0.9)
-# top_k = st.sidebar.slider("Top-K", min_value=1, max_value=100, value=50)
-# top_p = st.sidebar.slider("Top-P", min_value=0.1, max_value=1.0, value=0.95)
-# repetition_penalty = st.sidebar.slider("Repetition Penalty", min_value=1.0, max_value=10.0, value=2.0)
-# length_penalty = st.sidebar.slider("Length Penalty", min_value=0.1, max_value=10.0, value=1.7)
-# # early_stopping = st.sidebar.selectbox("Early Stopping", [True, False], index=0)
-
 generation_config = {
     "max_length": max_length,
     "num_beams": num_beams,
@@ -192,7 +209,7 @@ sample_text = st.selectbox("Select a sample text to test the model:", list(sampl
 task = st.selectbox("Select a task for the model:", list(task_options.keys()))
 
 # Conditionally show language options dropdown for diacritize and clean tasks
-if task in ["Diacritize text", "Clean text", "Translation"]:
+if task in ["Text Diacritization", "Text Cleaning", "Translation"]:
     language = st.selectbox("Select a Nigerian language:", list(language_options.keys()))
     task_value = f"{task_options[task]} {language_options[language]}"
 else: