README.md

---
library_name: transformers
language:
- en
- fr
- de
tags:
- v1.0.0
---


#### How to use

You can use this model with Transformers *pipeline* for NER.

<!-- Provide a longer summary of what this model is. -->
```python
from transformers import pipeline

MODEL_NAME = "emanuelaboros/lang-detect"

lang_pipeline = pipeline("lang-detect", model=MODEL_NAME, 
                        trust_remote_code=True,
                        device='cpu')

sentence = """En l'an 1348, au plus fort des ravages de la peste noire à travers l'Europe,
          le Royaume de France se trouvait à la fois au bord du désespoir et face à une opportunité."""

langs = lang_pipeline(sentence)
langs

```

```
{'label': 'fr', 'confidence': 99.87}
```
Works with lists of sentences also.

### BibTeX entry and citation info

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```