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---
pipeline_tag: token-classification
widget:
- text: سن نجورسن؟
example_title: Example 1
- text: من سنی سویرم.
example_title: Example 2
- text: سن شاهین قیزین چوخ سئویرسن.
example_title: Example 3
- text: آلما آلیب گلرم، سن هئچ بیر شی آلما.
example_title: Example 4
language:
- az
metrics:
- accuracy
- f1
---
# POS Tagger
- Type: Fine-tuned BERT-based Part-of-Speech (POS) tagging model
- Description: This model has been fine-tuned using [AzerBERT](https://huggingface.co/language-ml-lab/AzerBert) for part-of-speech tagging tasks in Iranian Azerbaijani text. It can be used to annotate text with 11 POS tags, which is essential for various downstream NLP applications.
## How to use
```python
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("token-classification", model="language-ml-lab/postagger-azb")
```
```python
# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("language-ml-lab/postagger-azb")
model = AutoModelForTokenClassification.from_pretrained("language-ml-lab/postagger-azb")
``` |