PLEASE-n_n

{"instruction": "If you are a Symptom Checker, please give the most appropriate diagnosis and department recommendations based on the patient's symptoms and medical history.", "input": "I had been going through...

{ "input": "###Instruction: ....\n\n###human: ....\n\n###chatbot: ....\n\n###human: ....\n\n###chatbot: ....\n\n###human: .....\n\n###chatbot:", "output": ".....###" } Thank you very much for the explanation. I am still a little confused about the training data structure...

python ./examples/chatbot.py --deepspeed configs/ds_config_chatbot.json --model_name_or_path ./finetuned_models/finetune_with_sym_chat --prompt_structure "###Instruction: If you are a Symptom Checker, please give the most appropriate diagnosis and department recommendations based on the patient's symptoms and medical...

I tried with --endstring "#". It works but sometimes the chatbot just repeats the same sentences. I am sure I put '###' as end marks in all training data as...

I am still a little confused about the prompt_structure. For example here in alpaca training data, _"text": "Input: Instruction: Give three tips for staying healthy. \n Output: 1.Eat a balanced...

Thank you for the explanation. However, I'm still a bit confused about the conversation dataset structure. For the training dataset, should I put the templated dataset as {"type": "text_only", "instances":...

Thank you for your explanation. I still have a question about how to build a chatbot. Whether I use the "type": "conversation" type of conversation data or the LLAMA3 template,...