Sentence Similarity
sentence-transformers
Safetensors
gemma3_text
Retrieval
STS
Classification
Clustering
Reranking
vllm
YanshekWoo commited on
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Update README.md

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fix: the prompt example in code

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  1. README.md +1 -11
README.md CHANGED
@@ -99,15 +99,9 @@ embeddings = model.encode(
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  show_progress_bar=True,
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  )
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  print(embeddings)
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- '''
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- [[-0.01867676 0.02319336 0.00280762 ... -0.02075195 0.00196838
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- -0.0703125 ]
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- [-0.0067749 0.03491211 0.01434326 ... -0.0043335 0.00509644
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- -0.04174805]]
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- '''
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  ```
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- Or you can use `encode_query` and `encode_document` to automatically add the default prompt for queries (`"Instruct: Given a query, retrieve documents that answer the query \n Query: "`) and documents (`""`), respectively.
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  ```python
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  from sentence_transformers import SentenceTransformer
@@ -137,10 +131,6 @@ document_embeddings = model.encode_document(documents)
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  similarities = model.similarity(query_embeddings, document_embeddings)
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  print(similarities)
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- '''
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- tensor([[0.9034, 0.2563],
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- [0.3153, 0.7396]])
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- '''
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  ```
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  ### vllm support
 
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  show_progress_bar=True,
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  )
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  print(embeddings)
 
 
 
 
 
 
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  ```
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+ Or you can use `encode_query` and `encode_document` to automatically add the default prompt for queries (`"Instruct: Given a query, retrieve documents that answer the query \nQuery: "`) and documents (`""`), respectively.
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  ```python
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  from sentence_transformers import SentenceTransformer
 
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  similarities = model.similarity(query_embeddings, document_embeddings)
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  print(similarities)
 
 
 
 
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  ```
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  ### vllm support