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updated description and Title

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  1. app.py +28 -16
app.py CHANGED
@@ -182,13 +182,18 @@ def interface():
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  # prompt = template_single.format(tab_name, textbox_prompt)
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  with gr.Tab("Linguistic Entities"):
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- gr.Markdown("<h2>πŸ“œ Rules<h2>")
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- gr.Markdown("<h4>- Enter a sentence for three models to process (Vicuna-7b, LLaMA-7b and GPT-3.5).</h4>")
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- gr.Markdown("<h4>- Enter your OpenAI Api Key and click on 'Submit Key'.</h4>")
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- gr.Markdown("<h4>- Select a Linguistic Entity from the Dropdown.</h4>")
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- gr.Markdown("<h4>- Click 'Submit' to send your inputs to the models.</h4>")
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- gr.Markdown("<h4>- Scroll to the bottom and click 'Clear' to start again.</h4>")
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- gr.Markdown("<h4>πŸ€– Now the models will output the linguistic entities found in your prompt based on your selections!</h4>")
 
 
 
 
 
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  # Inputs
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  ling_ents_prompt = gr.Textbox(show_label=False, placeholder="Write a prompt and press enter")
@@ -225,14 +230,18 @@ def interface():
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  # outputs=[linguistic_entities, ling_ents_prompt, gpt_ling_ents_chatbot])
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  with gr.Tab("POS/Chunking"):
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- gr.Markdown("<h2>πŸ“œ Rules</h2>")
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- gr.Markdown("<h4>- Enter a sentence for three models to process (Vicuna-7b, LLaMA-7b and GPT-3.5).</h4>")
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- gr.Markdown("<h4>- Enter your OpenAI Api Key and click on 'Submit Key'.</h4>")
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- gr.Markdown("<h4>- Select a Task from the Dropdown.</h4>")
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- gr.Markdown("<h4>- Select a Linguistic Entity from the Dropdown.</h4>")
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- gr.Markdown("<h4>- Click 'Submit' to send your inputs to the models.</h4>")
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- gr.Markdown("<h4>- Scroll to the bottom and click 'Clear' to start again.</h4>")
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- gr.Markdown("<h4>πŸ€– Now the models will output the POS Tagging or Chunking in your prompt with three Strategies based on your selections!</h4>")
 
 
 
 
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  # Inputs
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  task_prompt = gr.Textbox(show_label=False, placeholder="Write a prompt and press enter")
@@ -295,7 +304,10 @@ def interface():
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  # outputs=[task, task_prompt, gpt_S3_chatbot])
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  with gr.Blocks(theme=gr.themes.Soft()) as demo:
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- gr.Markdown("# LLM Evaluator With Linguistic Scrutiny")
 
 
 
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  # load interface
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  interface()
 
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  # prompt = template_single.format(tab_name, textbox_prompt)
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  with gr.Tab("Linguistic Entities"):
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+ gr.Markdown("""
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+ ##πŸ“œ Step-By-Step Instructions
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+
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+ - Enter a sentence for three models to process (Vicuna-7b, LLaMA-7b and GPT-3.5).
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+ - Enter your OpenAI Api Key and click on 'Submit Key'.
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+ - Select a Linguistic Entity from the Dropdown.
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+ - Click 'Submit' to send your inputs to the models.
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+ - Scroll to the bottom and click 'Clear' to start again.
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+
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+ ###πŸ€– Now the models will output the linguistic entities found in your prompt based on your selections!
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+
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+ """)
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  # Inputs
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  ling_ents_prompt = gr.Textbox(show_label=False, placeholder="Write a prompt and press enter")
 
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  # outputs=[linguistic_entities, ling_ents_prompt, gpt_ling_ents_chatbot])
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  with gr.Tab("POS/Chunking"):
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+ gr.Markdown("""
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+ ##πŸ“œ Step-By-Step Instructions
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+
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+ - Enter a sentence for three models to process (Vicuna-7b, LLaMA-7b and GPT-3.5).
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+ - Enter your OpenAI Api Key and click on 'Submit Key'.
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+ - Select a Task from the Dropdown.
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+ - Select a Linguistic Entity from the Dropdown.
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+ - Click 'Submit' to send your inputs to the models.
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+ - Scroll to the bottom and click 'Clear' to start again.
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+
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+ ### πŸ€– Now the models will output the POS Tagging or Chunking in your prompt with three Strategies based on your selections!
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+ """)
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  # Inputs
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  task_prompt = gr.Textbox(show_label=False, placeholder="Write a prompt and press enter")
 
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  # outputs=[task, task_prompt, gpt_S3_chatbot])
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  with gr.Blocks(theme=gr.themes.Soft()) as demo:
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+ gr.Markdown("""
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+ # Assessing the Articulate
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+ ## A Comparative Analysis of the Core Linguistic Knowledge in Large Language Models
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+ """)
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  # load interface
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  interface()