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--- |
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pipeline_tag: sentence-similarity |
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language: en |
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license: apache-2.0 |
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tags: |
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- sentence-transformers |
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- feature-extraction |
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- sentence-similarity |
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- transformers |
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--- |
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# hku-nlp/instructor-base |
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This is a general embedding model: It maps sentences & paragraphs to a 768 dimensional dense vector space. |
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The model was trained on diverse tasks. |
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It takes customized instructions and text inputs, and generates task-specific embeddings for general purposes, e.g., information retrieval, classification, clustering, etc. |
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``` |
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git clone https://github.com/HKUNLP/instructor-embedding |
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cd sentence-transformers |
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pip install -e . |
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``` |
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Then you can use the model like this: |
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```python |
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from sentence_transformers import SentenceTransformer |
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sentence = "3D ActionSLAM: wearable person tracking in multi-floor environments" |
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instruction = "Represent the Science title; Input:" |
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model = SentenceTransformer('hku-nlp/instructor-base') |
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embeddings = model.encode([[instruction,sentence,0]]) |
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print(embeddings) |
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``` |
