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@@ -9,27 +9,18 @@ Arabic language domain. This is the repository for the 7B-chat pretrained model.
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  ---
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  ## Model Details
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- We have released the AceGPT family of large language models, which is a collection of fully fine-tuned generative
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- text models based on LlaMA2, ranging from 7B to 13B parameters. Our models include two main categories: AceGPT
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- and AceGPT-chat. AceGPT-chat is an optimized version specifically designed for dialogue applications. It is worth
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- mentioning that our models have demonstrated superior performance compared to all currently available open-source
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- Arabic dialogue models in multiple benchmark tests. Furthermore, in our human evaluations, our models have shown
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- comparable satisfaction levels to some closed-source models, such as ChatGPT, in the Arabic language.
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  ## Model Developers
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- We are from the School of Data Science, the Chinese University of Hong Kong, Shenzhen (CUHKSZ), and
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- the Shenzhen Research Institute of Big Data (SRIBD).
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  ## Variations
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- AceGPT famils comes in a range of parameter sizes —— 7B and 13B, each size of model has a base categorie
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- and a -chat categorie.
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  ## Input
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  Models input text only.
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  ## Output
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  Models output text only.
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  ## Model Evaluation Results
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- Experiments on Arabic Vicuna-80, Arabic AlpacaEval. Numbers are the average perfor-mance ratio of ChatGPT
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- over three runs. We do not report results of raw Llama-2 models since they cannot properly generate Arabic
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- texts.
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  | | Arabic Vicuna-80 | Arabic AlpacaEval |
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  |------------------------------|--------------------|---------------------|
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  | Phoenix Chen et al. (2023a) | 71.92% ± 0.2% | 65.62% ± 0.3% |
 
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  ---
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  ## Model Details
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+ We have released the AceGPT family of large language models, which is a collection of fully fine-tuned generative text models based on LlaMA2, ranging from 7B to 13B parameters. Our models include two main categories: AceGPT and AceGPT-chat. AceGPT-chat is an optimized version specifically designed for dialogue applications. It is worth mentioning that our models have demonstrated superior performance compared to all currently available open-source Arabic dialogue models in multiple benchmark tests. Furthermore, in our human evaluations, our models have shown comparable satisfaction levels to some closed-source models, such as ChatGPT, in the Arabic language.
 
 
 
 
 
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  ## Model Developers
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+ We are from the School of Data Science, the Chinese University of Hong Kong, Shenzhen (CUHKSZ), and the Shenzhen Research Institute of Big Data (SRIBD).
 
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  ## Variations
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+ AceGPT famils comes in a range of parameter sizes —— 7B and 13B, each size of model has a base categorie and a -chat categorie.
 
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  ## Input
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  Models input text only.
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  ## Output
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  Models output text only.
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  ## Model Evaluation Results
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+ Experiments on Arabic Vicuna-80, Arabic AlpacaEval. Numbers are the average perfor-mance ratio of ChatGPT over three runs. We do not report results of raw Llama-2 models since they cannot properly generate Arabic texts.
 
 
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  | | Arabic Vicuna-80 | Arabic AlpacaEval |
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  |------------------------------|--------------------|---------------------|
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  | Phoenix Chen et al. (2023a) | 71.92% ± 0.2% | 65.62% ± 0.3% |