53 lines
2.2 KiB
Python
53 lines
2.2 KiB
Python
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"""
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Usage:
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python3 -m llava.model.make_delta --base ~/model_weights/llama-7b --target ~/model_weights/llava-7b --delta ~/model_weights/llava-7b-delta --hub-repo-id liuhaotian/llava-7b-delta
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"""
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import argparse
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import torch
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from tqdm import tqdm
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from transformers import AutoTokenizer, AutoModelForCausalLM
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from llava.model.utils import auto_upgrade
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def make_delta(base_model_path, target_model_path, delta_path, hub_repo_id):
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print("Loading base model")
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base = AutoModelForCausalLM.from_pretrained(
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base_model_path, torch_dtype=torch.float16, low_cpu_mem_usage=True)
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print("Loading target model")
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auto_upgrade(target_model_path)
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target = AutoModelForCausalLM.from_pretrained(target_model_path, torch_dtype=torch.float16, low_cpu_mem_usage=True)
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print("Calculating delta")
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for name, param in tqdm(target.state_dict().items(), desc="Calculating delta"):
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if name not in base.state_dict():
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assert name in ['model.mm_projector.weight', 'model.mm_projector.bias'], f'{name} not in base model'
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continue
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if param.data.shape == base.state_dict()[name].shape:
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param.data -= base.state_dict()[name]
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else:
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assert name in ['model.embed_tokens.weight', 'lm_head.weight'], f'{name} dimension mismatch: {param.data.shape} vs {base.state_dict()[name].shape}'
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bparam = base.state_dict()[name]
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param.data[:bparam.shape[0], :bparam.shape[1]] -= bparam
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print("Saving delta")
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if hub_repo_id:
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kwargs = {"push_to_hub": True, "repo_id": hub_repo_id}
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else:
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kwargs = {}
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target.save_pretrained(delta_path, **kwargs)
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target_tokenizer = AutoTokenizer.from_pretrained(target_model_path)
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target_tokenizer.save_pretrained(delta_path, **kwargs)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument("--base-model-path", type=str, required=True)
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parser.add_argument("--target-model-path", type=str, required=True)
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parser.add_argument("--delta-path", type=str, required=True)
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parser.add_argument("--hub-repo-id", type=str, default=None)
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args = parser.parse_args()
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make_delta(args.base_model_path, args.target_model_path, args.delta_path, args.hub_repo_id)
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