Apne Data Par AI: RAG Ya Fine-Tuning? 3 Sawaal
"Hamare data par AI chahiye" — 90% baar iska jawab fine-tuning nahi, RAG hai. Teen sawaal jo minaton mein faisla kar dete hain, aur dono ka asli kharcha.
Apne Data Par AI: RAG Ya Fine-Tuning? 3 Sawaal
Ye ek galti hai jo bahut mehngi padti hai. Team fine-tuning par mahine aur paisa laga deti hai, aur natija ye nikalta hai ki model ab lehja to sahi rakhta hai par tathya phir bhi galat batata hai — kyunki samasya lehje ki thi hi nahi.
Lehja badalna hai ya jaankari daalni hai?
Agar aap chahte hain ki model aapki company ki tarah bole, chhote jawab de, ya ek khaas format mein likhe — wo vyavhaar hai, aur uske liye fine-tuning banti hai. Agar aap chahte hain ki wo aapki price list jaane — wo jaankari hai, aur uske liye retrieval chahiye.
Aapka data kitni jaldi badalta hai?
Fine-tuning jaankari ko model ke andar pak kar band kar deti hai. Kal price badli to poora training dobara. RAG mein model sawaal ke waqt file padhta hai, isliye file badalte hi agla jawab apne aap sahi ho jaata hai.
Jawab ka source dikhana zaroori hai?
Fine-tuned model bata nahi sakta ki jawab kahan se aaya. RAG paragraph par ungli rakh sakta hai. Jahan koi faisla lena hai — policy, contract, medical, kanoon — wahan source dikhana hi ise istemaal layak banata hai.
| Aapko chahiye | Chuniye |
|---|---|
| Company ka lehja aur format | Fine-tuning |
| Apne documents se jawab | RAG |
| Har jawab ke saath source | RAG |
| Roz badalta hua data | RAG |
| Ek khaas kism ka output structure | Fine-tuning |
Pros
- RAG mein data kabhi bhi badal sakte hain
- Jawab ke saath source
- Model badalna aasaan
- Shuruaat sasti
Cons
- RAG ke liye documents saaf hone chahiye
- Scan ki hui PDF pehle OCR maangti hai
- Dono mein model ka kharcha lagta hi hai
Shuruaat kaise karein
Das document se shuru
Hazaar nahi. Chhote saaf set se hi pata chalta hai ki chalega ya nahi.
Aise sawaal poochhiye jinke jawab aapko pata hain
Galat jawab pakadne ka yahi ek tareeka hai.
Source dikhana chalu rakhiye
Bina source ke jawab par bharosa mat banaiye.
Fine-tuning tabhi, jab lehja bache
Jaankari theek hone ke baad hi ye sawaal uthaiye.
RAG ka poora naam kya hai?
Retrieval-Augmented Generation. Aasaan bhasha mein: pehle sahi paragraph dhoondho, phir usi se jawab likho.
Kya dono saath mein ho sakte hain?
Haan, aur bade setup mein aksar hote hain — jaankari RAG se, lehja fine-tuning se. Lekin shuruaat hamesha RAG se kijiye.
Hindi documents par chalega?
Haan. Dikkat mile-jule Hindi-English PDF aur scan ki hui files mein aati hai — unhe pehle test kar lijiye.
Save this summary as an image or share it.
AICreatorHub Team
The AICreatorHub editorial team is a group of hands-on AI practitioners, writers and developers based in India. We test AI tools and models ourselves, track official releases from OpenAI, Anthropic, Google, Meta and xAI, and translate them into simple, India-first guides in English and Hindi. Every article is written for real Indian use cases — pricing in rupees, free-tier tips and practical, tested steps — so you get accurate, up-to-date and genuinely useful AI information.