benchmarking suite

import transformers
from your_benchmarking_suite import run_benchmarks

def evaluate_new_model(model_name):
    model = transformers.AutoModelForSequenceClassification.from_pretrained(model_name)
    tokenizer = transformers.AutoTokenizer.from_pretrained(model_name)

    results = run_benchmarks(model, tokenizer)

    return results

# Evaluate a new model
new_model_results = evaluate_new_model("openai/gpt-4")

# Compare with current production model
if new_model_results['overall_score'] > current_model_results['overall_score']:
    print("New model outperforms current model. Consider updating.")
else:
    print("Current model still performs best. No action needed.")