45 lines
1.8 KiB
Python
45 lines
1.8 KiB
Python
#
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# Copyright 2016 The BigDL Authors.
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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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#
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import os
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import torch
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from transformers import AutoTokenizer
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import argparse
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current_dir = os.path.dirname(os.path.realpath(__file__))
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common_util_path = os.path.join(current_dir, '..')
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import sys
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sys.path.append(common_util_path)
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from common.utils import merge_adapter
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description='Merge the adapter into the original model for Llama2 model')
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parser.add_argument('--repo-id-or-model-path', type=str, default="meta-llama/Llama-2-7b-hf",
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help='The huggingface repo id for the Llama2 (e.g. `meta-llama/Llama-2-7b-hf` and `meta-llama/Llama-2-13b-chat-hf`) to be downloaded'
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', or the path to the huggingface checkpoint folder')
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parser.add_argument('--adapter_path', type=str,)
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parser.add_argument('--output_path', type=str,)
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args = parser.parse_args()
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base_model = model_path = args.repo_id_or_model_path
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adapter_path = args.adapter_path
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output_path = args.output_path
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tokenizer = AutoTokenizer.from_pretrained(base_model, trust_remote_code=True)
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merge_adapter(base_model, tokenizer, adapter_path, output_path)
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print(f'Finish to merge the adapter into the original model and you could find the merged model in {output_path}.')
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