---
language:
  - multilingual
  - de
  - en
  - fr
  - es
  - pl
  - ro
  - el
  - cs
  - bg
tags:
  - model2vec
  - embeddings
  - european
  - retail
license: mit
base_model: minishlab/M2V_multilingual_output
---

# m2v-multilingual-european

The [minishlab/M2V_multilingual_output](https://huggingface.co/minishlab/M2V_multilingual_output) model (distilled from [LaBSE](https://huggingface.co/sentence-transformers/LaBSE)), pruned to European languages only.

## What is this?

This is the original M2V multilingual model with all non-European script tokens removed. The base model was distilled from LaBSE (Language-agnostic BERT Sentence Embedding, 470M params) by the [MinishLab](https://github.com/MinishLab) team. We pruned the vocabulary to only keep European-script tokens.

## Stats

| | Before pruning | After pruning |
|---|---|---|
| Vocabulary | 501,054 tokens | 357,416 tokens |
| Model size | ~490 MB | ~350 MB |
| Embedding dim | 256 | 256 |

**28.7%** of tokens were removed (non-European scripts).

## Usage

```python
from model2vec import StaticModel

model = StaticModel.from_pretrained("flipbitsnotburgers/m2v-multilingual-european")
embeddings = model.encode(["deodorant", "Duschgel", "shower gel"])
```

## Pruned scripts

The following scripts were removed:
- CJK (Chinese, Japanese Kanji)
- Hangul (Korean)
- Hiragana & Katakana (Japanese)
- Arabic
- Hebrew
- Thai, Lao
- Devanagari, Bengali, Tamil, Telugu, and other Indic scripts
- Myanmar, Ethiopic, Tibetan, Khmer

## License

MIT (same as base model)