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base repository: codogogo/topfish
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head repository: umanlp/SemScale
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  • 3 commits
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Commits on Jan 16, 2024

  1. Update README.md

    fedenanni authored Jan 16, 2024
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Commits on Jul 7, 2025

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  2. Update README.md

    irehbein authored Jul 7, 2025
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4 changes: 2 additions & 2 deletions README.md
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@@ -29,7 +29,7 @@ The expected input is in the one-text-per-file format. Each text file in the ref

### (Multilingual) Word Embeddings

For an easy set-up, we provide pre-trained FastText embeddings in a single file for the following five language: English, French, German, Italian and Spanish, that can be obtained from [here](https://drive.google.com/file/d/1Oy61TV0DpruUXOK9qO3IFsvL5DMvwGwD/view?usp=sharing).
For an easy set-up, we provide pre-trained FastText embeddings in a single file for the following five language: English, French, German, Italian and Spanish, that can be obtained from [here](http://publications.wim.uni-mannheim.de/informatik/lski/semscale/embs/wiki.big-five.mapped.vec.bz2).

Nonetheless, you can easily use the tool for texts in other languages or with different word embeddings, as long as you:

@@ -54,7 +54,7 @@ The script requires basic libraries from the Python scientific stack: *numpy* (t
In the SemScale folder, just run the following command:

``
python scaler.py path-to-embeddings-file path-to-input-folder output.txt
python scaler.py path-to-input-folder path-to-embeddings-file output.txt
``

## Other functionalities