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--- |
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pipeline_tag: sentence-similarity |
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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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language: |
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- en |
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- fr |
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license: apache-2.0 |
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--- |
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## `semanlink_all_mpnet_base_v2` |
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This is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search. |
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`semanlink_all_mpnet_base_v2` has been fine-tuned on the knowledge graph [Semanlink](http://www.semanlink.net/sl/home?lang=fr) via the library [MKB](https://github.com/raphaelsty/mkb) on the link-prediction task. The model is dedicated to the representation of both technical and generic terminology in machine learning, NLP, news. |
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## Usage (Sentence-Transformers) |
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Using this model becomes easy when you have sentence-transformers installed: |
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``` |
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pip install -U sentence-transformers |
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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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sentences = ["Machine Learning", "Geoffrey Hinton"] |
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model = SentenceTransformer('raphaelsty/semanlink_all_mpnet_base_v2') |
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embeddings = model.encode(sentences) |
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print(embeddings) |
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``` |
