nagamesebert

from transformers import AutoTokenizer, AutoModel

model_name = "MWirelabs/nagamesebert"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModel.from_pretrained(model_name)

# Example usage
text = "Toi moi laga sathi hobo pare?"
inputs = tokenizer(text, return_tensors="pt")
outputs = model(**inputs)

from transformers import AutoModelForTokenClassification, TrainingArguments, Trainer

# Load model with classification head
model = AutoModelForTokenClassification.from_pretrained(
    "MWirelabs/nagamesebert",
    num_labels=num_labels
)

# Training arguments
training_args = TrainingArguments(
    output_dir="./results",
    num_train_epochs=100,
    per_device_train_batch_size=8,
    learning_rate=3e-5,
    weight_decay=0.01
)

# Train
trainer = Trainer(
    model=model,
    args=training_args,
    train_dataset=train_dataset,
    eval_dataset=eval_dataset
)
trainer.train()