#jupyter_notebook
Retrieval Augmented Generation (RAG) helps large language models (LLMs) answer questions using up-to-date or private information by connecting them to external data sources, unlike fine-tuning which retrains the model on specific data. RAG is useful when you need current, dynamic information without costly retraining, making it ideal for tasks like customer support or knowledge management. Fine-tuning is better for deep expertise in a specialized field but requires more data and effort. Using RAG lets you get accurate, relevant answers quickly by combining the model’s language skills with fresh, specific data, improving usefulness and reliability.
https://github.com/langchain-ai/rag-from-scratch
She's a mother, a daughter,
She's brave, courageous,
Is She's feeble ? Helpless ?
No! It's you, your frame of mind,
Still let's her freedom to rescind!
She's not disabled,
Just the scenario made her existence confined,
Even in the century of 21st,
She's still defenseless over the set of your mind!
She never got the freedom, which a boy gets at his age,
So could you please let me know,
How She's guilty at every stage ?
Either She's LAXMI to NIRBHAYA and PRIYANAKA in 2019,
Nothing has changed,
Every single day, every single minute, nd in every single second,
She's molested, burnt and raped!
This act is plaintive enough,
We can't even think of,
Only a question I wanted to ask,
When she'll get rid of!
💯
-Gurpreet Bhatia
#guri#poetry#review#write