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--- |
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pipeline_tag: token-classification |
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widget: |
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- text: سن نجورسن؟ |
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example_title: Example 1 |
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- text: من سنی سویرم. |
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example_title: Example 2 |
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- text: سن شاهین قیزین چوخ سئویرسن. |
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example_title: Example 3 |
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- text: آلما آلیب گلرم، سن هئچ بیر شی آلما. |
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example_title: Example 4 |
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language: |
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- az |
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metrics: |
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- accuracy |
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- f1 |
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--- |
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# POS Tagger |
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- Type: Fine-tuned BERT-based Part-of-Speech (POS) tagging model |
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- 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. |
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## How to use |
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```python |
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# Use a pipeline as a high-level helper |
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from transformers import pipeline |
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pipe = pipeline("token-classification", model="language-ml-lab/postagger-azb") |
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``` |
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|
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```python |
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# Load model directly |
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from transformers import AutoTokenizer, AutoModelForTokenClassification |
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tokenizer = AutoTokenizer.from_pretrained("language-ml-lab/postagger-azb") |
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model = AutoModelForTokenClassification.from_pretrained("language-ml-lab/postagger-azb") |
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``` |
