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Update README.md

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@@ -3,6 +3,7 @@ tags:
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  - sentence-transformers
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  - feature-extraction
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  - sentence-similarity
 
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  license: apache-2.0
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  datasets:
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  - wikimedia/wikipedia
@@ -15,7 +16,7 @@ metrics:
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  library_name: transformers
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  ---
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- # FractalGPT/SberDistil
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  This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search.
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  This is a fast and small model for solving the problem of determining the proximity between sentences, in the future we will reduce and speed it up. [Project](https://github.com/FractalGPT/ModelEmbedderDistilation)
@@ -38,7 +39,7 @@ from sentence_transformers import SentenceTransformer
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  ```
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  ```python
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- model = SentenceTransformer('FractalGPT/SberDistil')
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  def cos(x, y):
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  return np.dot(x, y)/(np.linalg.norm(x)*np.linalg.norm(y))
 
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  - sentence-transformers
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  - feature-extraction
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  - sentence-similarity
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+ - SbertDistil
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  license: apache-2.0
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  datasets:
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  - wikimedia/wikipedia
 
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  library_name: transformers
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  ---
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+ # FractalGPT/SbertDistil
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  This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search.
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  This is a fast and small model for solving the problem of determining the proximity between sentences, in the future we will reduce and speed it up. [Project](https://github.com/FractalGPT/ModelEmbedderDistilation)
 
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  ```
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  ```python
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+ model = SentenceTransformer('FractalGPT/SbertDistil')
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  def cos(x, y):
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  return np.dot(x, y)/(np.linalg.norm(x)*np.linalg.norm(y))