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@@ -2617,7 +2617,7 @@ pipeline_tag: feature-extraction
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  # mxbai-embed-large-v1
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- Here, we provide several ways to produce sentence embeddings. Please note that you have to provide the prompt `Represent this sentence for searching relevant passages:` for query if you want to use it for retrieval. Besides that you don't need any prompt. Our model also supports Matryoshka Representation Learning and binary or int8 quantization. [Learn More](https://www.mixedbread.ai/blog/binary-mrl)
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  ## Quickstart
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@@ -2633,7 +2633,7 @@ python -m pip install -U sentence-transformers
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  from sentence_transformers import SentenceTransformer
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  from sentence_transformers.util import cos_sim, quantize_embeddings
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- # 1. Specify preffered dimensions (default is 1024)
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  dimensions = 512
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  # 2. load model
 
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  # mxbai-embed-large-v1
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+ Here, we provide several ways to produce sentence embeddings. Please note that you have to provide the prompt `Represent this sentence for searching relevant passages:` for query if you want to use it for retrieval. Besides that you don't need any prompt. Our model also supports [Matryoshka Representation Learning and binary quantization](https://www.mixedbread.ai/blog/binary-mrl)
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  ## Quickstart
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  from sentence_transformers import SentenceTransformer
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  from sentence_transformers.util import cos_sim, quantize_embeddings
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+ # 1. Specify preffered dimensions
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  dimensions = 512
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  # 2. load model