| 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}') |
|
|
