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edited description strategies
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app.py
CHANGED
@@ -241,36 +241,37 @@ def interface():
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outputs=[linguistic_entities, ling_ents_prompt, vicuna_ling_ents_chatbot])
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with gr.Tab("CoreNLP"):
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gr.
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- If you
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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=[linguistic_entities, ling_ents_prompt, vicuna_ling_ents_chatbot])
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with gr.Tab("CoreNLP"):
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with gr.Row():
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gr.Markdown("""
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## π Step-By-Step Instructions
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- Enter a sentence for three models to process (Vicuna-7b, LLaMA-7b and GPT-3.5).
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- If you own an OpenAI API key, select 'Yes' in the dropdown. If you don't own one, select 'No'.
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- If you selected 'Yes', enter your OpenAI API Key [Link to your OpenAI keys](https://platform.openai.com/api-keys).
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- If you selected 'No', leave the 'OpenAI Key' field blank and continue with the rest.
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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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- To enter a new prompt, scroll to the bottom and click 'Clear' to start again.
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### β³ After you click 'Submit', the models will take a couple seconds to process your inputs.
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### π€ Then, the models will output the POS Tagging or Chunking in your prompt with three different strategies based on your selections!
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Note: If you get an 'Error' in the gpt-3.5 model, check the following:
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- Check that you entered your key correctly without any extra characters.
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- If you used a free key, it means you exceeded your quota from the free API Key.
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""")
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gr.Markdown("""
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### π οΈ How each Strategy works
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- Strategy 1 - QA-Based Prompting
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- S1 Explanation
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- Strategy 2 - Instruction-Based Prompting
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- S2 Explanation
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- Strategy 3 - Structured Prompting
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- S3 Explanation
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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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