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79a49d3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | import argparse
import os
import shutil
import torch
from internvl.model.internvl_chat import InternVLChatModel
parser = argparse.ArgumentParser()
parser.add_argument('base_model_path', type=str, help='Base InternVL checkpoint to keep projector and LLM from.')
parser.add_argument('vit_source_model_path', type=str, help='InternVL checkpoint to copy vision_model weights from.')
parser.add_argument('output_path', type=str, help='Output path for the merged checkpoint.')
args = parser.parse_args()
base_model = InternVLChatModel.from_pretrained(args.base_model_path, torch_dtype=torch.bfloat16)
vit_source_model = InternVLChatModel.from_pretrained(args.vit_source_model_path, torch_dtype=torch.bfloat16)
base_model.vision_model.load_state_dict(vit_source_model.vision_model.state_dict(), strict=True)
base_model.to(torch.bfloat16)
if os.path.exists(args.output_path):
shutil.rmtree(args.output_path)
os.makedirs(args.output_path, exist_ok=True)
base_model.save_pretrained(args.output_path, save_config=False)
for name in os.listdir(args.base_model_path):
src = os.path.join(args.base_model_path, name)
dst = os.path.join(args.output_path, name)
if name.startswith('model-') or name == 'model.safetensors' or name == 'model.safetensors.index.json':
continue
if os.path.isdir(src):
shutil.copytree(src, dst, dirs_exist_ok=True)
else:
shutil.copy2(src, dst)
print(f'finished: {args.output_path}')
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