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+ Quantization made by Richard Erkhov.
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+ [Github](https://github.com/RichardErkhov)
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+ [Discord](https://discord.gg/pvy7H8DZMG)
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+ [Request more models](https://github.com/RichardErkhov/quant_request)
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+ fairseq-dense-2.7B - bnb 8bits
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+ - Model creator: https://huggingface.co/KoboldAI/
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+ - Original model: https://huggingface.co/KoboldAI/fairseq-dense-2.7B/
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+ Original model description:
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+ ---
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+ language: en
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+ ---
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+ This is a Hugging Face transformers-compatible conversion of the original dense 2.7B-parameter model from the paper "[Efficient Large Scale Language Modeling with Mixtures of Experts](https://arxiv.org/abs/2112.10684)" from Artetxe et al. Please refer to the original model card, which can be found at https://github.com/facebookresearch/fairseq/blob/main/examples/moe_lm/model_card.md.
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+ # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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+ Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_KoboldAI__fairseq-dense-2.7B)
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+ | Metric | Value |
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+ |-----------------------|---------------------------|
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+ | Avg. | 33.67 |
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+ | ARC (25-shot) | 33.79 |
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+ | HellaSwag (10-shot) | 65.74 |
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+ | MMLU (5-shot) | 26.44 |
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+ | TruthfulQA (0-shot) | 34.57 |
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+ | Winogrande (5-shot) | 63.93 |
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+ | GSM8K (5-shot) | 0.0 |
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+ | DROP (3-shot) | 11.24 |
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