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@@ -2661,9 +2661,16 @@ Training data to train the models is released in its entirety. For more details,
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  ## Usage
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- Note `nomic-embed-text` requires prefixes! We support the prefixes `[search_query, search_document, classification, clustering]`.
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  For retrieval applications, you should prepend `search_document` for all your documents and `search_query` for your queries.
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  ### Sentence Transformers
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  ```python
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  from sentence_transformers import SentenceTransformer
 
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  ## Usage
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+ Note `nomic-embed-text` *requires* prefixes! We support the prefixes `[search_query, search_document, classification, clustering]`.
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  For retrieval applications, you should prepend `search_document` for all your documents and `search_query` for your queries.
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+ For example, you are building a RAG application over the top of Wikipedia. You would embed all Wikipedia articles with the prefix `search_document`
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+ and any questions you ask with `search_query`. For example:
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+ ```python
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+ queries = ["search_query: who is the first president of the united states?", "search_query: when was babe ruth born?"]
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+ documents = ["search_document: <article about US Presidents>", "search_document: <article about Babe Ruth>"]
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+ ```
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+
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  ### Sentence Transformers
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  ```python
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  from sentence_transformers import SentenceTransformer