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https://github.com/hiyouga/LLaMA-Factory.git
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@@ -4,32 +4,28 @@
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# Inspired by: https://huggingface.co/fireballoon/baichuan-llama-7b/blob/main/convert_baichuan_to_llama.py
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# Converted model: https://huggingface.co/hiyouga/Baichuan2-7B-Base-LLaMAfied
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import os
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import fire
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import json
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import torch
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from tqdm import tqdm
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import os
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from collections import OrderedDict
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from safetensors.torch import save_file
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from transformers.modeling_utils import (
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shard_checkpoint,
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SAFE_WEIGHTS_NAME,
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SAFE_WEIGHTS_INDEX_NAME,
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WEIGHTS_NAME,
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WEIGHTS_INDEX_NAME
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)
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from typing import Any, Dict, Optional
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import fire
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import torch
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from safetensors.torch import save_file
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from tqdm import tqdm
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from transformers.modeling_utils import (
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SAFE_WEIGHTS_INDEX_NAME,
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SAFE_WEIGHTS_NAME,
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WEIGHTS_INDEX_NAME,
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WEIGHTS_NAME,
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shard_checkpoint,
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)
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CONFIG_NAME = "config.json"
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def save_weight(
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input_dir: str,
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output_dir: str,
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shard_size: str,
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save_safetensors: bool
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):
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def save_weight(input_dir: str, output_dir: str, shard_size: str, save_safetensors: bool):
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baichuan2_state_dict: Dict[str, torch.Tensor] = OrderedDict()
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for filepath in tqdm(os.listdir(input_dir), desc="Load weights"):
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if os.path.isfile(os.path.join(input_dir, filepath)) and filepath.endswith(".bin"):
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@@ -41,8 +37,8 @@ def save_weight(
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if "W_pack" in key:
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proj_size = value.size(0) // 3
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llama2_state_dict[key.replace("W_pack", "q_proj")] = value[:proj_size, :]
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llama2_state_dict[key.replace("W_pack", "k_proj")] = value[proj_size:2*proj_size, :]
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llama2_state_dict[key.replace("W_pack", "v_proj")] = value[2*proj_size:, :]
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llama2_state_dict[key.replace("W_pack", "k_proj")] = value[proj_size : 2 * proj_size, :]
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llama2_state_dict[key.replace("W_pack", "v_proj")] = value[2 * proj_size :, :]
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elif "lm_head" in key:
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llama2_state_dict[key] = torch.nn.functional.normalize(value)
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else:
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@@ -56,7 +52,7 @@ def save_weight(
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save_file(shard, os.path.join(output_dir, shard_file), metadata={"format": "pt"})
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else:
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torch.save(shard, os.path.join(output_dir, shard_file))
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if index is None:
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print("Model weights saved in {}".format(os.path.join(output_dir, WEIGHTS_NAME)))
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else:
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@@ -66,10 +62,7 @@ def save_weight(
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print("Model weights saved in {}".format(output_dir))
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def save_config(
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input_dir: str,
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output_dir: str
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):
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def save_config(input_dir: str, output_dir: str):
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with open(os.path.join(input_dir, CONFIG_NAME), "r", encoding="utf-8") as f:
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llama2_config_dict: Dict[str, Any] = json.load(f)
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@@ -83,19 +76,14 @@ def save_config(
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print("Model config saved in {}".format(os.path.join(output_dir, CONFIG_NAME)))
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def llamafy_baichuan2(
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input_dir: str,
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output_dir: str,
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shard_size: str,
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save_safetensors: Optional[bool] = False
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):
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def llamafy_baichuan2(input_dir: str, output_dir: str, shard_size: str, save_safetensors: Optional[bool] = False):
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try:
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os.makedirs(output_dir, exist_ok=False)
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except Exception as e:
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raise print("Output dir already exists", e)
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save_weight(input_dir, output_dir, shard_size, save_safetensors)
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save_config(input_dir, output_dir)
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save_config(input_dir, output_dir)
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if __name__ == "__main__":
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