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---
language:
- bg
license: mit
pipeline_tag: token-classification
model-index:
- name: punctual-bert-bg
results: []
widget:
- text: 'Човекът искащ безгрижно писане ме помоли да създам този модел.'
---
# punctual-bert-bg
Visit the website - [Zapetayko](https://zapetayko.streamlit.app/), to test out the model.
## Usage
```python
from transformers import pipeline
MODEL_ID = "auhide/punctual-bert-bg"
punctuate = pipeline("token-classification", model=MODEL_ID, tokenizer=MODEL_ID)
punctuate("Човекът искащ безгрижно писане ме помоли да създам този модел.")
```
```bash
[{'entity': 'B-CMA',
'score': 0.95041466,
'index': 1,
'word': '▁Човекът',
'start': 0,
'end': 7},
{'entity': 'I-CMA',
'score': 0.95229745,
'index': 2,
'word': '▁иска',
'start': 7,
'end': 12},
{'entity': 'B-CMA',
'score': 0.95945585,
'index': 5,
'word': '▁писане',
'start': 23,
'end': 30},
{'entity': 'I-CMA',
'score': 0.90768945,
'index': 6,
'word': '▁ме',
'start': 30,
'end': 33}]
```
Basically, `B-CMA` tags the token that's before the comma, and `I-CMA` tags the token after the comma.
Therefore, if we place the commas based on these tags, the result is:
*"Човекът, искащ безгрижно писане, ме помоли да създам този модел."* |