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language: en
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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.

# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_KoboldAI__fairseq-dense-2.7B)

| Metric                | Value                     |
|-----------------------|---------------------------|
| Avg.                  | 33.67   |
| ARC (25-shot)         | 33.79          |
| HellaSwag (10-shot)   | 65.74    |
| MMLU (5-shot)         | 26.44         |
| TruthfulQA (0-shot)   | 34.57   |
| Winogrande (5-shot)   | 63.93   |
| GSM8K (5-shot)        | 0.0        |
| DROP (3-shot)         | 11.24         |