task = "ner"
model_checkpoint = "artiwise-ai/modernbert-base-tr-uncased"
batch_size = 8 
label_list = ['O', 'B-PER', 'I-PER', 'B-ORG', 'I-ORG', 'B-LOC', 'I-LOC']
max_length = 8192
learning_rate = 2e-5 
num_train_epochs = 5 
weight_decay = 0.01 

from transformers import AutoTokenizer, AutoModelForTokenClassification, pipeline
model = AutoModelForTokenClassification.from_pretrained("akdeniz27/modernbert-base-tr-uncased-ner")
tokenizer = AutoTokenizer.from_pretrained("akdeniz27/modernbert-base-tr-uncased-ner")
# tokenizer.model_max_length = 512 # Model max_length could be set here (max 8192 as default)
ner = pipeline("token-classification", model=model, tokenizer=tokenizer, aggregation_strategy="first")
ner("your text here")