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license: mit |
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base_model: |
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- meta-llama/Llama-2-7b-hf |
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The model is derived from Llama-2-7b-hf through pruning using LLM-Streamline **(Streamlining Redundant Layers to Compress Large Language Models, ICLR 2025 Spotlight)**. The entire training process required only 0.06B tokens. |
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Below are the results of the evaluation using lm-eval: |
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| | arc_c | arc_e | boolq | hellaswag | openbookqa | rte | winogrande | Avg | |
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|--------------|-------|-------|-------|-----------|------------|------|------------|------| |
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| Llama-2-7B | 43.3 | 76.4 | 77.7 | 57.2 | 31.4 | 62.8 | 69.1 | 59.7 | |
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| Llama-2-4.7B | 34.0 | 64.6 | 74.7 | 49.8 | 27.4 | 61.7 | 66.4 | 54.1 | |
