---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
language:
- en
- fr
license: apache-2.0
---

## `semanlink_all_mpnet_base_v2`

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.

`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.

## Usage (Sentence-Transformers)

Using this model becomes easy when you have sentence-transformers installed:

```
pip install -U sentence-transformers
```

Then you can use the model like this:

```python
from sentence_transformers import SentenceTransformer
sentences = ["Machine Learning", "Geoffrey Hinton"]

model = SentenceTransformer('raphaelsty/semanlink_all_mpnet_base_v2')
embeddings = model.encode(sentences)
print(embeddings)
```