Instructions to use MohammadKhosravi/Flair-Persian-NER-Finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Flair
How to use MohammadKhosravi/Flair-Persian-NER-Finetuned with Flair:
from flair.models import SequenceTagger tagger = SequenceTagger.load("MohammadKhosravi/Flair-Persian-NER-Finetuned") - Notebooks
- Google Colab
- Kaggle
NER Persian Legal Model
This model is trained for Named Entity Recognition on Persian texts using the Flair framework.
Training Data
Describe your dataset here.
Evaluation
Provide evaluation metrics here.
Usage
from flair.data import Sentence
from flair.models import SequenceTagger
# Load the model
tagger = SequenceTagger.load("MohammadKhosravi/Flair-Persian-NER-Finetuned")
# Create a sentence
sentence = Sentence("Your sample sentence here.")
# Predict NER tags
tagger.predict(sentence)
# Print the sentence with entities
print(sentence)
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Evaluation results
- F1 on Your Dataset Nameself-reportedYour F1 Score