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Update README.md

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  base_model: meta-llama/Meta-Llama-3-8B-Instruct
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  library_name: transformers
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  datasets:
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- - openbmb/UltraFeedback
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  tags:
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  - alignment-handbook
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  - llama
@@ -22,6 +22,8 @@ In comparison to the preference data construction method in our paper, it employ
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  2. When multiple outputs have the same highest score, the one with the shortest length is selected.
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  3. When multiple outputs have the same minimum score, the one with the smallest length difference from the chosen output is selected.
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  ### [AlpacaEval Eval Results](https://tatsu-lab.github.io/alpaca_eval/)
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  | Model | LC | WR | Avg. Length |
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  |-------------------------------------------|:------------:|:--------:|:-----------:|
 
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  base_model: meta-llama/Meta-Llama-3-8B-Instruct
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  library_name: transformers
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  datasets:
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+ - wzhouad/llama3-ultrafeedback-hybrid-v2
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  tags:
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  - alignment-handbook
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  - llama
 
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  2. When multiple outputs have the same highest score, the one with the shortest length is selected.
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  3. When multiple outputs have the same minimum score, the one with the smallest length difference from the chosen output is selected.
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+ The model is trained based on [wzhouad/llama3-ultrafeedback-hybrid-v2](https://huggingface.co/datasets/wzhouad/llama3-ultrafeedback-hybrid-v2).
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+
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  ### [AlpacaEval Eval Results](https://tatsu-lab.github.io/alpaca_eval/)
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  | Model | LC | WR | Avg. Length |
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  |-------------------------------------------|:------------:|:--------:|:-----------:|