Update app.py

app.py

@@ -108,6 +108,17 @@ def generate_response(query, history, model, temperature, max_tokens, top_p, see
     return response
 
 
+# gr.Markdown("""
+# ### 1. Attention Is All You Need (Vaswani et al., 2017)
+# This groundbreaking paper introduced the **Transformer** architecture. It revolutionized natural language processing by enabling parallelization and significantly improving performance on tasks like translation, leading to models like *BERT* and *GPT*.
+
+# ### 2. Generative Adversarial Nets (Goodfellow et al., 2014)
+# This paper proposed **GANs**, a novel framework for generative modeling using two neural networks—a generator and a discriminator—that compete in a zero-sum game.  
+
+# ### 3. Parameter-Efficient Transfer Learning for NLP (Houlsby et al., 2019)
+# This paper introduces **adapter modules**, a method for fine-tuning large pre-trained language models with significantly fewer parameters.  
+# """)
+
 
 additional_inputs = [
     gr.Dropdown(choices=["llama-3.3-70b-versatile", "llama-3.1-8b-instant", "llama3-70b-8192", "llama3-8b-8192", "mixtral-8x7b-32768", "gemma2-9b-it"], value="gemma2-9b-it", label="Model"),