readme: ---
  license: apache-2.0
  ---
  # Cross-Encoder for MS Marco
  
  This model is a generic masked language model fine tuned on stack overflow data.  It's base pre-trained model was the cross-encoder/ms-marco-MiniLM-L-12-v2 model.
  
  The model can be used for creating vectors for search applications.  It was trained to be used in conjunction with a knn search with OpenSearch for a pet project I've been working on.  It's easiest to create document embeddings with the flair package as shown below.
  
  
  ## Usage with Transformers
  
  ```python
  from flair.data import Sentence
  from flair.embeddings import TransformerDocumentEmbeddings
  
  sentence = Sentence("Text to be embedded.")
  model = TransformerDocumentEmbeddings("model-name")
  model.embed(sentence)
  embeddings = sentence.embedding
  ```
  