Feature(LLMLingua): add note

app.py

@@ -6,6 +6,9 @@ llm_lingua = PromptCompressor("lgaalves/gpt2-dolly", device_map="cpu")
 INTRO = """
 # LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models
 This is an early demo of the prompt compression method LLMLingua.
+
+It should be noted that due to limited resources, we only provide the **GPT2-Small** size language model in this demo. Using the **LLaMA2-7B** as a small language model would result in a significant performance improvement, especially at high compression ratios.
+
 To use it, upload your prompt and set the compression target.
 1. ✅ Set the different components of the prompt separately, including instruction, context, and question. Leave the corresponding field empty if a particular component does not exist.
     - Question: This refers to the directives given by the user to the LLMs, such as inquiries, questions, or requests. Positioned after the instruction and context modules, the question module has a high sensitivity to compression.