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  # 🪆mxbai-embed-2d-large-v1🪆
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- This is our [2DMSE](https://arxiv.org/abs/2402.14776) sentence embedding model. It supports the adaptive transformer layer and embedding size. Find out more in our [blog post](https://mixedbread.ai/blog/2d-mse).
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  TLDR: TLDR: 2D-🪆 allows you to shrink the model and the embeddings layer. Shrinking only the embeddings model yields competetive results to other models like [nomics embeddings model](https://huggingface.co/nomic-ai/nomic-embed-text-v1.5). Shrinking the model to ~50% maintains upto 85% of the performance without further training.
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  ## Evaluation
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- Please find more information in our [blog post](https://mixedbread.ai/blog/2d-mse)
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  ## Community
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  Please join our [Discord Community](https://discord.gg/jDfMHzAVfU) and share your feedback and thoughts! We are here to help and also always happy to chat.
 
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  # 🪆mxbai-embed-2d-large-v1🪆
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+ This is our [2DMSE](https://arxiv.org/abs/2402.14776) sentence embedding model. It supports the adaptive transformer layer and embedding size. Find out more in our [blog post](https://mixedbread.ai/blog/mxbai-embed-2d-large-v1).
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  TLDR: TLDR: 2D-🪆 allows you to shrink the model and the embeddings layer. Shrinking only the embeddings model yields competetive results to other models like [nomics embeddings model](https://huggingface.co/nomic-ai/nomic-embed-text-v1.5). Shrinking the model to ~50% maintains upto 85% of the performance without further training.
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  ## Evaluation
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+ Please find more information in our [blog post](https://mixedbread.ai/blog/mxbai-embed-2d-large-v1).
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  ## Community
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  Please join our [Discord Community](https://discord.gg/jDfMHzAVfU) and share your feedback and thoughts! We are here to help and also always happy to chat.