initial readme
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README.md
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license: llama3
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license: llama3
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---
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# 🔹 Key Highlights:
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- 12% Fewer Parameters: nyun-llama3-62B comprises approximately 12% fewer parameters than the popular Llama-3-70B.
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- Intact Performance: Despite having fewer parameters, our model performs at par if not better, and occasionally outperforms, the Llama-3-70B.
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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-Llama3-62B | Meta-Llama3-70B | Meta-Llama2-70B | MBZUAI K2-65B |
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| --- | --- | --- | --- | --- |
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| MMLU (5-shot) | 78.9 | 79.5 | 69.7 | 67.9 |
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| Winogrande (5-shot) | 83.3 | 83.1 | 81.8 | 77.0 |
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| BoolQ (0-shot) | 85.3 | 79.0 | 73.1 | 83.0 |
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| Hellaswag (10-shot) | 85.8 | 88.0 | 86.9 | 85.5 |
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| Arc Challenge (25-shot) | 65.9 | 68.8 | 67.2 | 64.8 |
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| GSM8K (5-shot) | 70.9 | 76.9 | 52.6 | 50.2 |
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| Average | 78.4 | 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)
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