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9bd15f1937
* TensorRT-LLM Release 0.10.0 --------- Co-authored-by: Loki <lokravi@amazon.com> Co-authored-by: meghagarwal <16129366+megha95@users.noreply.github.com>
61 lines
2.1 KiB
Python
61 lines
2.1 KiB
Python
# SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: Apache-2.0
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import argparse
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import os
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import time
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import tensorrt_llm
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from tensorrt_llm.models import Phi3ForCausalLM, PhiForCausalLM
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def parse_arguments():
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parser = argparse.ArgumentParser()
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parser.add_argument('--model_dir', type=str, default=None)
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parser.add_argument('--dtype',
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type=str,
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default='float16',
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choices=['float32', 'bfloat16', 'float16'])
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parser.add_argument('--output_dir',
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type=str,
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default='tllm_checkpoint',
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help='The path to save the TensorRT-LLM checkpoint')
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parser.add_argument(
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'--model_type',
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type=str,
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default='phi-2',
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choices=['phi-2', 'Phi-3-mini-4k-instruct', 'Phi-3-mini-128k-instruct'],
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help='Model to be converted.')
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args = parser.parse_args()
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return args
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if __name__ == '__main__':
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print(tensorrt_llm.__version__)
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args = parse_arguments()
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tik = time.time()
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if not os.path.exists(args.output_dir):
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os.makedirs(args.output_dir)
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modelForCausalLM = PhiForCausalLM if args.model_type == "phi-2" else Phi3ForCausalLM
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modelForCausalLM.convert_hf_checkpoint(args.model_dir,
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dtype=args.dtype,
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output_dir=args.output_dir)
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tok = time.time()
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t = time.strftime('%H:%M:%S', time.gmtime(tok - tik))
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print(f'Total time of converting checkpoints: {t}')
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