LLaMA-Factory-310P3/prepare_yaml_file.py

54 lines
1.7 KiB
Python

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