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@@ -7,7 +7,7 @@ base_model:
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  - Qwen/Qwen3-4B-Thinking-2507
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  ---
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- # DMind-2: Edge-Deployed Web3 Investment Intelligence Model
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  ## Model Overview
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@@ -21,23 +21,14 @@ DMind2-mini: Edge deployment for maximum privacy and zero-latency analysis on pe
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  DMind2-base: Professional trading terminals and workstations
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  DMind2-large: Enterprise and institutional deployment
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- ## Model Variants
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- ### DMind2-mini
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  - **Base Model**: Qwen3-4B-Thinking-2507
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  - **Parameters**: 4B
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  - **Training Duration**: 1 month of refined post-training
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  - **Hardware Requirements**: Minimum 4GB VRAM, supports consumer-grade GPUs
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- - **Inference Speed**: Single analysis response <2 seconds (RTX 3060)
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  - **Features**: Optimized for edge deployment, achieving extreme lightweight while maintaining professional analysis capabilities
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- ### DMind2-base (Coming Soon)
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- - **Parameters**: 8B
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- - **Target Scenario**: Professional trading terminal deployment
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-
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- ### DMind2-large (Coming Soon)
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- - **Parameters**: 14B
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- - **Target Scenario**: Institutional-grade private deployment
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  ## Technical Innovations
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  - Qwen/Qwen3-4B-Thinking-2507
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  ---
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+ # DMind-2: Advanced Web3 Domain-Specific Large Language Models
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  ## Model Overview
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  DMind2-base: Professional trading terminals and workstations
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  DMind2-large: Enterprise and institutional deployment
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+ ## Model Variants(DMind2-mini)
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  - **Base Model**: Qwen3-4B-Thinking-2507
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  - **Parameters**: 4B
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  - **Training Duration**: 1 month of refined post-training
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  - **Hardware Requirements**: Minimum 4GB VRAM, supports consumer-grade GPUs
 
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  - **Features**: Optimized for edge deployment, achieving extreme lightweight while maintaining professional analysis capabilities
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  ## Technical Innovations
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