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examples/example_finetune_args.yaml

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examples/finetune.sh

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llmsql/__init__.py

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LLMSQL — A Text2SQL benchmark for evaluation of Large Language Models
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"""
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__version__ = "0.1.6"
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__version__ = "0.1.7"
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def __getattr__(name: str): # type: ignore

llmsql/__main__.py

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import argparse
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import inspect
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import json
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import sys
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def main() -> None:
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parser = argparse.ArgumentParser(prog="llmsql", description="LLMSQL CLI")
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subparsers = parser.add_subparsers(dest="command")
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# ================================================================
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# Fine-tuning command
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# ================================================================
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ft_parser = subparsers.add_parser(
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"finetune",
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help="Fine-tune a causal LM on the LLMSQL benchmark.",
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description="Launch fine-tuning using Hugging Face TRL's SFTTrainer.\n\n"
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"You can pass parameters directly on the CLI or provide a YAML "
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"config file via --config-file. CLI args take precedence.",
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epilog="Example:\n llmsql finetune --config-file examples/example_finetune_args.yaml",
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)
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ft_parser.add_argument(
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"--config-file",
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type=str,
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required=True,
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help="Path to a YAML config file containing training parameters.",
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)
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# ================================================================
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# Inference command
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# ================================================================
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# ================================================================
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args, extra = parser.parse_known_args()
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# ------------------------------------------------
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# Fine-tune
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# ------------------------------------------------
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if args.command == "finetune":
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from llmsql.finetune import finetune
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sys.argv = ["llmsql-finetune"] + extra + ["--config_file", args.config_file]
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finetune.run_cli()
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# ------------------------------------------------
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# Inference
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# ------------------------------------------------
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elif args.command == "inference":
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if args.command == "inference":
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if args.method == "vllm":
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from llmsql import inference_vllm as inference_fn
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elif args.method == "transformers":

pyproject.toml

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[project]
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name = "llmsql"
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version = "0.1.6"
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version = "0.1.7"
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description = "A Text2SQL benchmark for evaluation of Large Language Models"
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keywords = ["llm", "sql", "benchmark", "evaluation", "ai", "nlp"]
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authors = [

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