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license: apache-2.0 |
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# Cross-Encoder for MS Marco |
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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. |
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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. |
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## Usage with Transformers |
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```python |
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from flair.data import Sentence |
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from flair.embeddings import TransformerDocumentEmbeddings |
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sentence = Sentence("Text to be embedded.") |
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model = TransformerDocumentEmbeddings("model-name") |
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model.embed(sentence) |
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embeddings = sentence.embedding |
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``` |
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