Update README.md

README.md

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 Safety alignment is another aspect we particularly emphasize. The crypto investment field is full of high-risk, high-reward opportunities, and the model must accurately identify and highlight potential risks. We use proprietary risk case datasets to conduct safety training on the model, ensuring it won't output overly optimistic investment advice or overlook obvious risk signals. For example, when analyzing an emerging DeFi protocol, the model automatically checks key risk indicators such as smart contract audit status, team background, and total value locked, explicitly marking risk levels in investment recommendations. This responsible output approach not only protects users' asset security but also reflects our commitment to financial compliance.
 
 ## Performance Metrics
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+  <img src="dmind-2-performance.jpeg" width="70%" alt="DMind-2" />
+</div>
 
 | Category | Benchmark (Metric) | DeepSeek-R1-0528-Qwen3-8B | gpt-oss-20b | Qwen3-32B | Qwen3-4B(Thinking) | DMind-2-4B(4B) |
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