Update README.md

README.md

@@ -1,3 +1,29 @@
----
-license: llama3
----
+---
+license: llama3
+---
+# 🔹 Key Highlights:
+
+- 14% Fewer Parameters: nyun-llama3-60B comprises approximately 14% fewer parameters than the popular Llama-3-70B.
+- Intact Performance: Despite having fewer parameters, our model performs at par if not better, and occasionally outperforms, the Llama-3-70B.
+- No Fine-Tuning Required: This model undergoes no fine-tuning, showcasing the raw potential of our optimization techniques.
+
+## Pipeline and Collaboration
+
+For insights into the pipeline and the list of methods used to optimize these models, check out our PruneGPT repository (https://github.com/nyunAI/PruneGPT). 
+We invite companies and organizations interested in joining forces with us to release more such open-source variants to reach out at [email protected].
+
+### Model Performance
+
+| Dataset | Nyun-Llama3-60B | Meta-Llama3-70B | Meta-Llama2-70B | MBZUAI K2-65B |
+| --- | --- | --- | --- | --- |
+| MMLU (5-shot) | 78.6 | 79.5 | 69.7 | 67.9 |
+| Winogrande (5-shot) | 83.4 | 83.1 | 81.8 | 77.0 |
+| BoolQ (0-shot) | 85.2 | 79.0 | 73.1 | 83.0 |
+| Hellaswag (10-shot) | 85.7 | 88.0 | 86.9 | 85.5 |
+| Arc Challenge (25-shot) | 64.4 | 68.8 | 67.2 | 64.8 |
+| GSM8K (5-shot) | 68.7 | 76.9 | 52.6 | 50.2 |
+| Average | 77.7 | 79.2 |  71.9 | 71.4 |
+
+
+- **Developed by:** [Nyun AI](https://nyunai.com/)
+- **Repository:** [Github](https://github.com/nyunAI/PruneGPT)