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---
language:
- multilingual
- pl
- ru
- uk
- bg
- cs
- sl
datasets:
- SlavicNER
license: apache-2.0
library_name: transformers
pipeline_tag: text2text-generation
tags:
- lemmatization
widget:
- text: "pl:Polsce"
- text: "cs:Velké Británii"
- text: "bg:българите"
- text: "ru:Великобританию"
- text: "sl:evropske komisije"
- text: "uk:Європейського агентства лікарських засобів"
---
# Model description
This is a baseline model for named entity **lemmatization** trained on the single-out topic split of the
[SlavicNER corpus](https://github.com/SlavicNLP/SlavicNER).
# Resources and Technical Documentation
- Paper: [Cross-lingual Named Entity Corpus for Slavic Languages](https://arxiv.org/pdf/2404.00482), to appear in LREC-COLING 2024.
- Annotation guidelines: https://arxiv.org/pdf/2404.00482
- SlavicNER Corpus: https://github.com/SlavicNLP/SlavicNER
# Evaluation
*Will appear soon*
# Usage
You can use this model directly with a pipeline for text2text generation:
```python
from transformers import pipeline
model_name = "SlavicNLP/slavicner-lemma-single-out-large"
pipe = pipeline("text2text-generation", model_name)
texts = ["pl:Polsce", "cs:Velké Británii", "bg:българите", "ru:Великобританию", "sl:evropske komisije",
"uk:Європейського агентства лікарських засобів"]
outputs = pipe(texts)
lemmas = [o['generated_text'] for o in outputs]
print(lemmas)
# ['Polska', 'Velká Británie', 'българи', 'Великобритания', 'evropska komisija', 'Європейське агентство лікарських засобів']
```
# Citation
*Will appear soon*
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