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[to #50334474] llama tuned model -> pipeline

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Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/13071602
* prepare for inference
This commit is contained in:
suluyan.sly
2023-06-26 22:49:44 +08:00
committed by wenmeng.zwm
parent 6ab85256af
commit 7e28ca226b
1 changed files with 16 additions and 0 deletions
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16
examples/pytorch/llama/finetune_llama.py
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@@ -261,3 +261,19 @@ if __name__ == '__main__':
trainer = build_trainer(
name=Trainers.text_generation_trainer, default_args=kwargs)
trainer.train()
# prepare for inference
if int(os.environ.get('LOCAL_RANK', 0)) == 0:
tokenizer.save_pretrained(os.path.join(args.work_dir, 'output'))
os.system(f'rm {args.work_dir}/output/pytorch_model*')
os.system(
f'python3 {args.work_dir}/zero_to_fp32.py {args.work_dir} {args.work_dir}/output/pytorch_model.bin'
)
os.system(
f'cp {model_path}/configuration.json {args.work_dir}/output/configuration.json'
)
with open(f'{model_path}/config.json', 'r') as f:
config = json.load(f)
config['vocab_size'] = len(tokenizer)
with open(f'{args.work_dir}/output/config.json', 'w') as f:
json.dump(config, f)