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README.md
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@@ -51,23 +51,8 @@ The model is the instruction-tuned version of [`rinna/youri-7b`](https://hugging
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# Benchmarking
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| Model | Model type | 4-task score | 6-task score | 8-task score |
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| rinna/youri-7b-instruction | SFT | 83.88 | 80.93 | 63.63 |
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| **rinna/youri-7b-chat** | **SFT** | **78.29** | **78.47** | **62.18** |
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| matsuo-lab/weblab-10b-instruction-sft | SFT | 78.75 | 75.05 | 59.11 |
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| rinna/youri-7b | pre-trained | 73.32 | 74.58 | 58.87 |
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| stabilityai/japanese-stablelm-instruct-alpha-7b | SFT | 70.10 | 71.32 | 54.71 |
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| elyza/ELYZA-japanese-Llama-2-7b | pre-trained | 71.72 | 69.28 | 53.17 |
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| elyza/ELYZA-japanese-Llama-2-7b-instruct | SFT | 70.57 | 68.12 | 53.14 |
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| stabilityai/japanese-stablelm-base-alpha-7b | pre-trained | 61.03 | 65.83 | 51.05 |
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| matsuo-lab/weblab-10b | pre-trained | 66.33 | 65.58 | 50.74 |
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| meta/llama2-7b | pre-trained | 56.33 | 54.80 | 42.97 |
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| rinna/japanese-gpt-neox-3.6b | pre-trained | 47.20 | 54.68 | 41.80 |
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| rinna/bilingual-gpt-neox-4b | pre-trained | 46.60 | 52.04 | 40.03 |
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# How to use the model
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# Benchmarking
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Please refer to [rinna's LM benchmark page](https://rinnakk.github.io/research/benchmarks/lm/index.html).
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# How to use the model
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