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@@ -145,7 +145,7 @@ The following factors can influence MAI-DS-R1's behavior and performance:
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  - **Harm Mitigation**: MAI-DS-R1 outperforms both R1-1776 and the original R1 model in minimizing harmful content.
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  ### Model Architecture and Objective
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- - **Model Name**: MAI-DS-R1 (671B)
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  - **Architecture**: Based on DeepSeek-R1, a transformer-based autoregressive language model utilizing multi-head self-attention and Mixture-of-Experts (MoE) for scalable and efficient inference.
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  - **Objective**: Post-trained to reduce CCP-aligned restrictions and enhance harm protection, while preserving the original model’s strong chain-of-thought reasoning and general-purpose language understanding capabilities.
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  - **Pre-trained Model Base**: DeepSeek-R1 (671B)
 
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  - **Harm Mitigation**: MAI-DS-R1 outperforms both R1-1776 and the original R1 model in minimizing harmful content.
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  ### Model Architecture and Objective
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+ - **Model Name**: MAI-DS-R1
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  - **Architecture**: Based on DeepSeek-R1, a transformer-based autoregressive language model utilizing multi-head self-attention and Mixture-of-Experts (MoE) for scalable and efficient inference.
150
  - **Objective**: Post-trained to reduce CCP-aligned restrictions and enhance harm protection, while preserving the original model’s strong chain-of-thought reasoning and general-purpose language understanding capabilities.
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  - **Pre-trained Model Base**: DeepSeek-R1 (671B)