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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-125M - bnb 4bits
+- Model creator: https://huggingface.co/KoboldAI/
+- Original model: https://huggingface.co/KoboldAI/fairseq-dense-125M/
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+Original model description:
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+language: en
+---
+This is a Hugging Face transformers-compatible conversion of the original dense 125M-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)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_KoboldAI__fairseq-dense-125M)
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+| Metric                | Value                     |
+|-----------------------|---------------------------|
+| Avg.                  | 26.0   |
+| ARC (25-shot)         | 24.06          |
+| HellaSwag (10-shot)   | 34.14    |
+| MMLU (5-shot)         | 23.98         |
+| TruthfulQA (0-shot)   | 43.72   |
+| Winogrande (5-shot)   | 50.59   |
+| GSM8K (5-shot)        | 0.0        |
+| DROP (3-shot)         | 5.5         |
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