Original data from:
https://huggingface.co/datasets/BI55/MedText

I just reformat it for fine tunning in lamma2 based on this article https://mlabonne.github.io/blog/posts/Fine_Tune_Your_Own_Llama_2_Model_in_a_Colab_Notebook.html

Another important point related to the data quality is the prompt template. Prompts are comprised of similar elements: system prompt (optional) to guide the model, user prompt (required) to give the instruction, additional inputs (optional) to take into consideration, and the model’s answer (required). In the case of Llama 2, the authors used the following template for the chat models:

[INST] 
User prompt [/INST] Model answer
license:cc-by-4.0 region:us
{"license": "cc-by-4.0"}
TAGS
#license-cc-by-4.0 #region-us 

Original data from:
URL

I just reformat it for fine tunning in lamma2 based on this article URL

Another important point related to the data quality is the prompt template. Prompts are comprised of similar elements: system prompt (optional) to guide the model, user prompt (required) to give the instruction, additional inputs (optional) to take into consideration, and the model’s answer (required). In the case of Llama 2, the authors used the following template for the chat models:

[INST] 
User prompt [/INST] Model answer
TAGS
#license-cc-by-4.0 #region-us 

passage: TAGS
#license-cc-by-4.0 #region-us 
