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Comment by iamarunbrahma | Hacker News Reader

This is a toy project. Hence, large-scale collection of data and pre-processing them into conversational format, also removing sensitive information is not possible. I was able to curate only 172 rows of data.

I have shared a notebook and explained detailed steps in my blog - https://medium.com/@iamarunbrahma/fine-tuning-of-falcon-7b-l.... If you are interested to replicate the steps on medical-domain therapy chat transcripts, you are definitely welcome. If you face any issues during fine-tuning steps, you can connect with me on my blog. Would love to help out!

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It is interesting. Sorry to pour so much cold water on the topic, it's more the application than the code that people have issue with.

I wonder if retrieval augmented generation would be appropriate here too. Fast, scalable. Fine-tuning is comparatively pretty expensive.

Thanks for sharing your code, iamarunbrahma.

The purpose of this project was to showcase how can we fine-tune large models on a free-tier GPU provided by Colab. Hence, any individual can utilize parameter-efficient fine-tuning methods to tune LLMs on domain-specific datasets.

RAG and fine-tuning serves a slightly different purpose. Fine-tuning helps LLM in learning a new task/skill such as question/answering task, summarization task etc, and improving reliability at producing a desired output such as JSON format structure thereby reducing dependency on prompt engineering.

On the other hand, RAG provides you with external domain-specific knowledge, which one can leverage to get latest information.

I see, thank you for the explanation. RAG is also appropriate for question/answering but I do see your point. Can see myself returning to your code for inspiration soon.

> I was able to curate only 172 rows of data

Skill issue - focus more on data integrity & less on HN clout

Oh!! So, you want every individual who post their github repo on HN; to collect dataset like billions of dollars funded startups and make a reliable chatbot which not a single well funded startup or listed NASDAQ companies could have done. I salute you.

OP is sharing a personal project, he's not claiming he's solved the mental health crisis.

This is Hacker News. These types of projects are half of the reason I come here, what's with the hate?

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