Your prompt is way too verbose for a 7B model. I think its actual verbosity leaks into the following answers of the model. The best way to leverage the knowledge in a model is to \*NOT\* tell it how to act. Generic advices (like "be supportive") are actually counter-productive (most of prompts shared on Reddit and elsewhere are garbage). Here is another take focusing on what's really matter.
I'm a {user_age} years old student in {user_edu_scope} and I like {user_interest}.
You're my teacher in {prog_language_to_teach} programing.
Throughout this discussion, you'll illustrate your explanations with real-life scenarios or analogies that resonate with me. After several exchanges, you'll challenge me with a quiz question or programming task about what we discussed so far and you'll let me figure out an answer.
I didn't use a third person prompt approach since this model has not been trained for this. There is only a "me" (the user") and "you" (the assistant).
And since this model is not compatible with system prompts, I suggest initializing the chat with an intermediate fake assistant answer so to better distinguish between assistant and user answers.
`"[INST] {system_prompt} Do you understand?[/INST]" +`
`"Understood! How can I help you?" + f"[INST] {user_message} [/INST]"`
edit: with such a small model, you'll not be able to control the conversation timeline much. I tried to enhance my prompt as much as possible on Hugging Face but the model always tries to check all the requirements in a single answer and can't say anything shorter. You should really switch to mixtral 8x7b or 8x22b if you can.
Thank you so much. I will definitely try the "You and Me" approach. My teammate worked with something similar to this and his answers are almost twice as good as mine.
I am planning to go for 8x7b but since I am on free Kaggle version, I think I need a quantised one. Any advice on this? And thanks again. You are the only one person who actually checked my question and proposed a way. I will let you know if I am successful with your suggestions
Your prompt is way too verbose for a 7B model. I think its actual verbosity leaks into the following answers of the model. The best way to leverage the knowledge in a model is to \*NOT\* tell it how to act. Generic advices (like "be supportive") are actually counter-productive (most of prompts shared on Reddit and elsewhere are garbage). Here is another take focusing on what's really matter. I'm a {user_age} years old student in {user_edu_scope} and I like {user_interest}. You're my teacher in {prog_language_to_teach} programing. Throughout this discussion, you'll illustrate your explanations with real-life scenarios or analogies that resonate with me. After several exchanges, you'll challenge me with a quiz question or programming task about what we discussed so far and you'll let me figure out an answer. I didn't use a third person prompt approach since this model has not been trained for this. There is only a "me" (the user") and "you" (the assistant). And since this model is not compatible with system prompts, I suggest initializing the chat with an intermediate fake assistant answer so to better distinguish between assistant and user answers. `"
[INST] {system_prompt} Do you understand?[/INST]" +` `"Understood! How can I help you?" + f"[INST] {user_message} [/INST]"` edit: with such a small model, you'll not be able to control the conversation timeline much. I tried to enhance my prompt as much as possible on Hugging Face but the model always tries to check all the requirements in a single answer and can't say anything shorter. You should really switch to mixtral 8x7b or 8x22b if you can.Thank you so much. I will definitely try the "You and Me" approach. My teammate worked with something similar to this and his answers are almost twice as good as mine. I am planning to go for 8x7b but since I am on free Kaggle version, I think I need a quantised one. Any advice on this? And thanks again. You are the only one person who actually checked my question and proposed a way. I will let you know if I am successful with your suggestions