metadata

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 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

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("token-classification", model="language-ml-lab/postagger-azb")

# 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")