remove finetune.py script

scripts/finetune.py

@@ -1,50 +0,0 @@
-"""Prepare and train a model on a dataset. Can also infer from a model or merge lora."""
-
-import logging
-from pathlib import Path
-
-import fire
-import transformers
-
-from axolotl.cli.art import print_axolotl_text_art
-from axolotl.cli.checks import check_accelerate_default_config, check_user_token
-from axolotl.cli.config import load_cfg
-from axolotl.cli.datasets import load_datasets
-from axolotl.cli.inference import do_inference
-from axolotl.cli.merge_lora import do_merge_lora
-from axolotl.cli.shard import shard
-from axolotl.common.cli import TrainerCliArgs
-from axolotl.train import train
-
-LOG = logging.getLogger("axolotl.scripts.finetune")
-
-
-def do_cli(config: Path = Path("examples/"), **kwargs):
-    print_axolotl_text_art()
-    LOG.warning(
-        str(
-            PendingDeprecationWarning(
-                "scripts/finetune.py will be replaced with calling axolotl.cli.train"
-            )
-        )
-    )
-    parsed_cfg = load_cfg(config, **kwargs)
-    check_accelerate_default_config()
-    check_user_token()
-    parser = transformers.HfArgumentParser(TrainerCliArgs)
-    parsed_cli_args, _ = parser.parse_args_into_dataclasses(
-        return_remaining_strings=True
-    )
-    if parsed_cli_args.inference:
-        do_inference(cfg=parsed_cfg, cli_args=parsed_cli_args)
-    elif parsed_cli_args.merge_lora:
-        do_merge_lora(cfg=parsed_cfg)
-    elif parsed_cli_args.shard:
-        shard(cfg=parsed_cfg)
-    else:
-        dataset_meta = load_datasets(cfg=parsed_cfg, cli_args=parsed_cli_args)
-        train(cfg=parsed_cfg, dataset_meta=dataset_meta)
-
-
-if __name__ == "__main__":
-    fire.Fire(do_cli)