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+ ---
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+ license: llama2
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+ datasets:
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+ - JeanKaddour/minipile
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+ language:
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+ - en
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+ ---
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+ Meta's Llama 3 70B pruned to 42B parameters using the methodology described in [The Unreasonable Ineffectiveness of the Deeper Layers](https://arxiv.org/abs/2403.17887). Post-pruning trained using QLoRA for ~100M tokens from [JeanKaddour/minipile](https://huggingface.co/datasets/JeanKaddour/minipile).
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+ Layers to prune selected using [PruneMe](https://github.com/arcee-ai/PruneMe).
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+ Still evaluating, don't get too excited! Might be incredibly dumb. Check out these zero-shot MMLU numbers though:
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+ | Groups |Version|Filter|n-shot|Metric|Value | |Stderr|
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+ |------------------|-------|------|-----:|------|-----:|---|-----:|
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+ |mmlu |N/A |none | 0|acc |0.7319|± |0.0034|
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+ | - humanities |N/A |none | 0|acc |0.6582|± |0.0063|
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+ | - other |N/A |none | 0|acc |0.7927|± |0.0069|
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+ | - social_sciences|N/A |none | 0|acc |0.8466|± |0.0064|
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+ | - stem |N/A |none | 0|acc |0.6702|± |0.0079|