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  ```
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- # Evaluation
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-
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- Evaluation to come.
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-
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  # FAQ
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  **Q: Is this Model better than V2?**
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  **A:** Broadly speaking, when going from 1024 to 512 dimensions, there is very little trade-off (1 percent). When going down to 64 dimensions, you may face a decrease of up to 3 percent.
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  # Up next:
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  German_Semantic_V3_Instruct: Guiding your embeddings towards self-selected aspects
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  ```
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  # FAQ
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  **Q: Is this Model better than V2?**
 
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  **A:** Broadly speaking, when going from 1024 to 512 dimensions, there is very little trade-off (1 percent). When going down to 64 dimensions, you may face a decrease of up to 3 percent.
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+ ## Evaluation
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+
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+ Storage comparison:
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/5f3801ab7e583543386217ac/Aa5WzHanj-DXc86AKxpEz.png)
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+ Benchmarks: soon.
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+
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  # Up next:
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  German_Semantic_V3_Instruct: Guiding your embeddings towards self-selected aspects
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