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README.md
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# Evaluation
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Evaluation to come.
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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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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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# Up next:
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German_Semantic_V3_Instruct: Guiding your embeddings towards self-selected aspects
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