---
license: apache-2.0
language:
- it
- fr
- de
- es
- en
base_model:
- google-bert/bert-base-multilingual-cased
pipeline_tag: text-classification
library_name: transformers
---

# 🌍 Multilingual Intent Classifier – Language Switching

This model is a fine-tuned multilingual BERT (`bert-base-multilingual-cased`) for intent **classification** of **language-switching** requests.  
It recognizes when a user wants to change the conversation language and supports 5 language:

- `english`
- `italian`
- `german`
- `spanish`
- `french`


## It recognizes even other class of text like:

- `other` (generic sentences not related to language switching)
- `not_allowed` (unsupported languages)


## 📊 Training Data

- ~6,000 training examples
- Short conversational sentences (e.g. "Can we switch to English?", "Vorrei parlare in italiano", "Nein, bitte auf Deutsch"), and pieaces of conversation steps
- Languages covered: English, Italian, German, Spanish, French
- `not_allowed` and `other` provide robustness for real-world inputs
---

## 🚀 Usage with 🤗 Transformers

You can use the model directly with the `pipeline` API:

```python
from transformers import pipeline

# Replace with the actual model repo
model_name = "software-si/change-language-intent"

classifier = pipeline(
    task="text-classification",
    model=model_name,
    tokenizer=model_name,
    return_all_scores=True
)

texts = [
    "Vorrei parlare in italiano",
    "Can we switch to English?",
    "Nein, bitte auf Deutsch"
]

results = classifier(texts)

for text, res in zip(texts, results):
    print(f"\nInput: {text}")
    for r in res:
        print(f"  {r['label']}: {r['score']:.4f}")