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@@ -23,7 +23,7 @@ These quantized models offer improved efficiency while maintaining performance.
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  ## Original Model Information
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  - **Name**: [Nxcode-CQ-7B-orpo](https://huggingface.co/NTQAI/Nxcode-CQ-7B-orpo)
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- - **Base Model**: Qwen/CodeQwen1.5-7B
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  - **Fine-tuning Approach**: Monolithic Preference Optimization without Reference Model
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  - **Fine-tuning Data**: 100k samples of high-quality ranking data
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  - **Model Type**: Transformer-based decoder-only language model
 
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  ## Original Model Information
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  - **Name**: [Nxcode-CQ-7B-orpo](https://huggingface.co/NTQAI/Nxcode-CQ-7B-orpo)
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+ - **Base Model**: [Qwen/CodeQwen1.5-7B](https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat)
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  - **Fine-tuning Approach**: Monolithic Preference Optimization without Reference Model
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  - **Fine-tuning Data**: 100k samples of high-quality ranking data
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  - **Model Type**: Transformer-based decoder-only language model