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license: llama3 |
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# 🔹 Key Highlights: |
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- 13% Fewer Parameters: nyun-c2-llama3-61B comprises approximately 13% fewer parameters than the popular Llama-3-70B. |
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- Better Performance: Despite having fewer parameters, this model performs better than Llama3-70B on multiple benchmarks. |
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- No Fine-Tuning Required: This model undergoes no fine-tuning, showcasing the raw potential of our optimization techniques. |
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## Pipeline and Collaboration |
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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). |
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We invite companies and organizations interested in joining forces with us to release more such open-source variants to reach out at [email protected]. |
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### Model Performance |
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| Dataset | nyun-c2-llama3-61B | Meta-Llama3-70B | Meta-Llama2-70B | MBZUAI K2-65B | |
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| --- | --- | --- | --- | --- | |
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| MMLU (5-shot) | 78.8 | 79.5 | 69.7 | 67.9 | |
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| Winogrande (5-shot) | 86.2 | 83.1 | 81.8 | 77.0 | |
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| BoolQ (0-shot) | 85.1 | 79.0 | 73.1 | 83.0 | |
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| Hellaswag (10-shot) | 87.4 | 88.0 | 86.9 | 85.5 | |
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| Arc Challenge (25-shot) | 67.6 | 68.8 | 67.2 | 64.8 | |
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| GSM8K (5-shot) | 79.4 | 76.9 | 52.6 | 50.2 | |
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| Average | 80.7 | 79.2 | 71.9 | 71.4 | |
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- **Developed by:** [Nyun AI](https://nyunai.com/) |
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- **Repository:** [Github](https://github.com/nyunAI/PruneGPT) |
