Update app.py

app.py

@@ -9,15 +9,9 @@ tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
 num_new_tokens = 200  # change to the number of new tokens you want to generate
 
 DESCRIPTION = """\
-# 🧑🏽‍💻Microsoft Phi2 Chatbot🤖
-This Space demonstrates model [Microsoft Phi2 2.7B](https://huggingface.co/microsoft/phi-2), a model with 2.78B parameters fine-tuned for chat instructions. Feel free to play with it, or duplicate to run generations without a queue! If you want to run your own service, you can also [deploy the model on Inference Endpoints](https://huggingface.co/inference-endpoints).
-\n 🔎 For more details about the finetuning, take a look at the [GitHub](https://github.com/mkthoma/llm_finetuning) code.
-\n ⛔⛔ The model is hosted on a CPU and inference takes a long time. Please feel free to duplicate the space and use it on a GPU ⛔⛔
-"""
+# Microsoft Phi2 Chatbot
+\n The model is hosted on a CPU and inference takes a long time. Please feel free to duplicate the space and use it on a GPU"""
 
-LICENSE = """
-As a derivate work of [Microsoft Phi2 2.7B](https://huggingface.co/microsoft/phi-2), this demo is governed by the original [license](https://huggingface.co/microsoft/phi-2/resolve/main/LICENSE).
-"""
 
 def generate(question, context, max_new_tokens = 200, temperature = 0.6):
   
@@ -37,7 +31,7 @@ def generate(question, context, max_new_tokens = 200, temperature = 0.6):
 bbchatbot = gr.Chatbot(
     avatar_images=["logo/user_logo.png", "logo/bot_logo.png"], bubble_full_width=False, show_label=False, show_copy_button=True, likeable=True,)
 
-examples = [["What is a large language model?"], ["How to calm down a person?"], ["What is aritificial intelligence?"], ["How to write a good resume?"]]
+examples = [["What are transformers?"], ["What are LLMs"], ["What is machine learning?"], ["How to write a good resume?"]]
 
 additional_inputs =  additional_inputs=[gr.Slider(label="Max new tokens",minimum=100,maximum=500,step=10,value=num_new_tokens),
                                         gr.Slider(label="Temperature",minimum=0.1,maximum=4.0,step=0.1,value=0.6)]