Below is a section of log, which is about an agent completing a task. The task is a python script using a language model to generate answer for a question. If the agent encountered an error, the user can provide feedback to correct the error. Please extract the correct operation steps to complete the task and each operation step must be a python script or shell that can be excuted. Next time, agent can use the correct operation step to complete task without human feedback 

SYSTEM: Human feedback: the large language model is in local path, /root/work/llm_model/llama-65b-hf
NEXT ACTION: COMMAND = write_to_file ARGUMENTS = {'filename': '/root/Auto-GPT/autogpt/auto_gpt_workspace/question_answer.py', 'text': "import torch\nfrom transformers import AutoTokenizer, AutoModelForSeq2SeqLM\n\nmodel_path = '/root/work/llm_model/llama-65b-hf'\ntokenizer = AutoTokenizer.from_pretrained(model_path)\nmodel = AutoModelForSeq2SeqLM.from_pretrained(model_path)\n\nquestion = 'who are you?'\n\ninputs = tokenizer.encode_plus(question, return_tensors='pt')\noutputs = model.generate(**inputs)\nanswer = tokenizer.decode(outputs[0], skip_special_tokens=True)\n\nwith open('answer.txt', 'w') as f:\n f.write(answer)\n"}
SYSTEM: Command write_to_file returned: File written to successfully.
NEXT ACTION: COMMAND = execute_python_file ARGUMENTS = {'filename': '/root/Auto-GPT/autogpt/auto_gpt_workspace/question_answer.py'}
SYSTEM: Human feedback: please use AutoModelForCausalLM instead of AutoModelForSeq2SeqLM, and you can use pipeline for "text-generation"
NEXT ACTION: COMMAND = write_to_file ARGUMENTS = {'filename': '/root/Auto-GPT/autogpt/auto_gpt_workspace/question_answer.py', 'text': "import torch\nfrom transformers import AutoTokenizer, AutoModelForCausalLM, pipeline\n\nmodel_path = '/root/work/llm_model/llama-65b-hf'\ntokenizer = AutoTokenizer.from_pretrained(model_path)\nmodel = AutoModelForCausalLM.from_pretrained(model_path)\n\ntext_generator = pipeline('text-generation', model=model, tokenizer=tokenizer)\n\nquestion = 'who are you?'\n\nanswer = text_generator(question, max_length=50, do_sample=True, num_return_sequences=1)[0]['generated_text']\n\nwith open('answer.txt', 'w') as f:\n f.write(answer)\n"}
SYSTEM: Command write_to_file returned: File written to successfully.
NEXT ACTION: COMMAND = execute_python_file ARGUMENTS = {'filename': '/root/Auto-GPT/autogpt/auto_gpt_workspace/question_answer.py'}
SYSTEM: Command execute_python_file returned:
NEXT ACTION: COMMAND = read_file ARGUMENTS = {'filename': '/root/Auto-GPT/autogpt/auto_gpt_w You should write your response with 350 or more words.
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