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Listing all dependencies directly in setup.py to fix workflow
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README.md

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# BenchTool
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A lightweight tool to benchmark the performance of NLP models based on medical text datasets. Supports HuggingFace, ONNX, and ORT models, and works with input data from CSV files or a PostgreSQL database.
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A lightweight tool to benchmark the performance of NLP models based on medical text datasets. Supports HuggingFace, ONNX, and ORT models, and works with input data from a CSV file.
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## Features
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- Compare multiple NLP models
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- Supports HuggingFace, ONNX, and ORT model types
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- Input from CSV or PostgreSQL database
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- Input from CSV
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- Outputs performance metrics like inference time and throughput
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- Configurable via a single YAML file
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setup.py

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packages=find_packages(include=['utils', 'utils.*']),
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py_modules=['main', 'benchmark'],
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install_requires=[
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r.strip() for r in open('requirements.txt').readlines() if r.strip() and not r.startswith('#')
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'aiohappyeyeballs',
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'aiohttp',
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'aiosignal',
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'attrs',
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'certifi',
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'charset-normalizer',
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'click',
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'coloredlogs',
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'datasets',
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'dill',
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'dlib',
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'face-recognition',
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'face_recognition_models',
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'filelock',
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'flatbuffers',
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'frozenlist',
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'fsspec',
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'huggingface-hub',
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'humanfriendly',
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'idna',
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'Jinja2',
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'MarkupSafe',
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'mpmath',
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'multidict',
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'multiprocess',
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'networkx',
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'numpy',
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'onnx',
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'onnxruntime',
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'opencv-python',
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'optimum',
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'packaging',
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'pandas',
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'pillow',
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'propcache',
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'protobuf',
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'pyarrow',
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'python-dateutil',
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'pytz',
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'PyYAML',
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'regex',
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'requests',
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'safetensors',
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'setuptools',
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'six',
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'sympy',
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'tokenizers',
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'torch',
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'tqdm',
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'transformers',
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'typing_extensions',
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'tzdata',
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'urllib3',
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'xxhash',
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'yarl',
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],
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entry_points={
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'console_scripts': [

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