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export_hf_checkpoint.py
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48 lines (39 loc) · 1.67 KB
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# SPDX-FileCopyrightText: Copyright (c) 2023-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Export a HF checkpoint (with ModelOpt state) for deployment."""
import argparse
import torch
from transformers import AutoModelForCausalLM
import modelopt.torch.opt as mto
from modelopt.torch.export import export_hf_checkpoint
def parse_args():
parser = argparse.ArgumentParser(
description="Export a HF checkpoint (with ModelOpt state) for deployment."
)
parser.add_argument("--model_path", type=str, default="Path of the trained checkpoint.")
parser.add_argument(
"--export_path", type=str, default="Destination directory for exported files."
)
return parser.parse_args()
mto.enable_huggingface_checkpointing()
args = parse_args()
model = AutoModelForCausalLM.from_pretrained(args.model_path, torch_dtype="auto")
model.eval()
with torch.inference_mode():
export_hf_checkpoint(
model, # The quantized model.
export_dir=args.export_path, # The directory where the exported files will be stored.
)
print(f"Exported checkpoint to {args.export_path}")