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m2v-multilingual-european
flipbitsnotburgers/m2v-multilingual-european
m2v-multilingual-european is a machine learning model from flipbitsnotburgers. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for model2vec. The card lists the license as mit.
The minishlab/M2Vmultilingualoutput model (distilled from LaBSE), pruned to European languages only.
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366 MB on disk
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At a glance
- Library
- model2vec
- License
- mit
- Model type
- model2vec
- Access
- Public
- Created
- Apr 16, 2026
- Updated
- Apr 16, 2026
- SHA
- 90bc9d18
Base models
Model card
From the Hugging Face model README
m2v-multilingual-european
The minishlab/M2V_multilingual_output model (distilled from 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 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
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)
- Library
- model2vec
- Type
- model2vec
- License
- mit
- Languages
- multilingual, de, en, fr, es, pl
- Created
- Apr 16, 2026
- Updated
- Apr 16, 2026