| | --- |
| | license: mit |
| | --- |
| | |
| | These word embeddings were computed using the POLAR technique to reproject 'common' word embeddings into roundabout 700 interpretable dimensions of polar opposites (i.e. good/bad). |
| | I just used their scripts here: |
| | https://github.com/Sandipan99/POLAR |
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| | I applied those on the wikidata5m embeddings, 5 million knowledge graph embeddings (SimplE). |
| | https://graphvite.io/docs/latest/pretrained_model.html |
| | |
| | As the model became too huge, I further filtered it for overlap with fasttext embedding tokens. |
| | Not all dimensions make sense, this is a work in progress. |
| | I intend to remove dimensions which turn out to not make sense, when using them. |
