|
--- |
|
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) |
