54 lines
1.6 KiB
Python
54 lines
1.6 KiB
Python
import sys
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import yaml
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def main():
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run_type = sys.argv[1]
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model = sys.argv[2]
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max_steps = sys.argv[3]
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run_name = sys.argv[4]
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output_dir = sys.argv[5]
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if run_type == "lora_sft":
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yaml_file = './results/lora_sft_template.yaml'
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elif run_type == "inference":
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yaml_file = './results/predict_template.yaml'
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model_name_or_path = ""
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template = ""
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if model == "9g-8B":
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model_name_or_path = "ms_cache/hub/qy/sft_8b_v2"
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template = "default"
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elif model == "Baichuan2-7B":
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model_name_or_path = "ms_cache/hub/baichuan-inc/Baichuan2-7B-Base"
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template = "baichuan2"
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elif model == "ChatGLM2-6B":
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model_name_or_path = "ms_cache/hub/zhipuai/chatglm2-6b"
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template = "chatglm2"
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elif model == "Llama2-7B":
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model_name_or_path = "ms_cache/hub/modelscope/llama-2-7b-ms"
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template = "llama2"
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elif model == "Qwen-7B":
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model_name_or_path = "../../../models/qwen"
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template = "qwen"
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else:
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print("ERROR: model not supported.")
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sys.exit()
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config = None
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with open(yaml_file, 'r', encoding='utf-8') as f:
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config = yaml.load(f.read(), Loader=yaml.FullLoader)
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config['model_name_or_path'] = model_name_or_path
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config['template'] = template
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config['output_dir'] = output_dir
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if run_type == "lora_sft":
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config['max_steps'] = int(max_steps)
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with open(f'{output_dir}/{run_name}.yaml', 'w', encoding='utf-8') as f:
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yaml.dump(data=config, stream=f, allow_unicode=True)
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print(f"yaml file saved to {output_dir}/{run_name}.yaml")
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if __name__ == "__main__":
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main() |