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	convert : fix remote option in Windows (#14100)
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		@@ -6389,8 +6389,8 @@ def parse_args() -> argparse.Namespace:
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        help="model is executed on big endian machine",
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    )
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    parser.add_argument(
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        "model", type=Path,
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        help="directory containing model file",
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        "model", type=str,
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        help="directory containing model file or huggingface repository ID (if --remote)",
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        nargs="?",
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    )
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    parser.add_argument(
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@@ -6493,18 +6493,20 @@ def main() -> None:
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    else:
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        logging.basicConfig(level=logging.INFO)
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    dir_model = args.model
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    if args.remote:
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        hf_repo_id = args.model
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        from huggingface_hub import snapshot_download
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        local_dir = snapshot_download(
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            repo_id=str(dir_model),
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            repo_id=hf_repo_id,
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            allow_patterns=["LICENSE", "*.json", "*.md", "*.txt", "tokenizer.model"])
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        dir_model = Path(local_dir)
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        logger.info(f"Downloaded config and tokenizer to {local_dir}")
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    else:
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        hf_repo_id = None
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        dir_model = Path(args.model)
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    if not dir_model.is_dir():
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        logger.error(f'Error: {args.model} is not a directory')
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        logger.error(f'Error: {dir_model} is not a directory')
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        sys.exit(1)
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    ftype_map: dict[str, gguf.LlamaFileType] = {
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@@ -6524,9 +6526,9 @@ def main() -> None:
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    if args.outfile is not None:
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        fname_out = args.outfile
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    elif args.remote:
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    elif hf_repo_id:
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        # if remote, use the model ID as the output file name
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        fname_out = Path("./" + str(args.model).replace("/", "-") + "-{ftype}.gguf")
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        fname_out = Path("./" + hf_repo_id.replace("/", "-") + "-{ftype}.gguf")
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    else:
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        fname_out = dir_model
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@@ -6555,7 +6557,7 @@ def main() -> None:
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                                     split_max_tensors=args.split_max_tensors,
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                                     split_max_size=split_str_to_n_bytes(args.split_max_size), dry_run=args.dry_run,
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                                     small_first_shard=args.no_tensor_first_split,
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                                     remote_hf_model_id=str(args.model) if args.remote else None)
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                                     remote_hf_model_id=hf_repo_id)
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        if args.vocab_only:
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            logger.info("Exporting model vocab...")
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