Update README.md

README.md

@@ -80,7 +80,7 @@ tokenizer = AutoTokenizer.from_pretrained(model_name)
 
 prompt = "What are the key regulatory considerations for a company planning to conduct an initial public offering (IPO) in the United States?"
 messages = [
-    {"role": "system", "content": "You are an expert financial assistant - specializing in governance and regulatory domains."},
+    {"role": "system", "content": "You are Llama-3-SEC, a financial analyst. Never mention your inability to access real-time information."},
     {"role": "user", "content": prompt}
 ]
 text = tokenizer.apply_chat_template(
@@ -139,7 +139,7 @@ This release represents the initial checkpoint of the Llama-3-SEC model, trained
 
 The model is available for both commercial and non-commercial use under the Llama-3 license. We encourage users to explore the model's capabilities and provide feedback to help us continuously improve its performance and usability. For more information - please see our detailed blog on Llama-3-SEC.
 
-**Note:** We trained Llama-3-SEC to be very compliant with system prompts. We have included a default system prompt, but if you wish to tailor answers to what your specific use case is, creating a system prompt that outlines your desired behavior is recommended.
+**Note:** We trained Llama-3-SEC to be very compliant with system prompts. We've had the best results with avoiding the use of "AI" in the system prompt, and further instructing it to not mention its lack of real-time information.
 
 **Disclaimer:** Llama-3-SEC is a large language model (LLM) designed to assist with SEC data analysis. Users are solely responsible for any actions taken as a result of using Llama-3-SEC. Always double-check model responses.