# # model_quantizer.py

# from transformers import AutoModelForSequenceClassification
# from optimum.onnxruntime import ORTOptimizer, ORTModelForSequenceClassification
# from optimum.onnxruntime.configuration import OptimizationConfig

# model = ORTModelForSequenceClassification.from_pretrained(
#     "Essay-Grader/roberta-ai-detector-20250401_232702",
#     from_transformers=True
#  )

# optimizer = ORTOptimizer.from_pretrained(model)
# optimization_config = OptimizationConfig(
#     optimization_level=99,
#     enable_transformers_specific_optimizations=True,
#     optimize_for_gpu=True,
#     fp16=True
# )

# optimizer.optimize(
#     save_dir="./optimized_model",
#     optimization_config=optimization_config
# )