Update README.md

README.md

@@ -5,13 +5,17 @@ pipeline_tag: text-generation
 base_model: unsloth/Qwen2.5-3B-Instruct
 ---
 
+
 # Commgpt‑3B
 
-**Commgpt‑3B** is a conversational language model fine-tuned from [unsloth/Qwen2.5-3B-Instruct](https://huggingface.co/unsloth/Qwen2.5-3B-Instruct).  
-It was specifically adapted for **Engineering Communications** topics.
+**Commgpt‑3B** is a conversational language model fine-tuned from [unsloth/Qwen2.5-3B-Instruct](https://huggingface.co/unsloth/Qwen2.5-3B-Instruct), adapted specifically for **Advanced Communication Systems (EECE 442)** at the American University of Beirut.
+
+The model was trained using a curriculum of domain-specific Q&A pairs and evaluated on a custom benchmark of 450 communication systems questions. It was originally deployed with a retrieval-augmented generation (RAG) pipeline and Gradio interface.
+
+This repo contains **only the model weights** and a **detailed implementation report**.
 
-For more information, visit the GitHub repository:  
-🔗 [https://github.com/DavidA00/Commgpt-final-year-project](https://github.com/DavidA00/Commgpt-final-year-project)
+📄 Full report and documentation:  
+[https://github.com/DavidA00/Commgpt-final-year-project](https://github.com/DavidA00/Commgpt-final-year-project)
 
 ## Usage
 
@@ -22,5 +26,5 @@ model = AutoModelForCausalLM.from_pretrained("dabboud/Commgpt-3B")
 tokenizer = AutoTokenizer.from_pretrained("dabboud/Commgpt-3B")
 
 generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
-output = generator("Hello, how can I help you today?", max_new_tokens=100)
+output = generator("What is Nyquist rate?", max_new_tokens=100)
 print(output[0]["generated_text"])