1. Home
  2. Detail

@montyhilal7:

Monty Farfoor 🇸🇩
Monty Farfoor 🇸🇩
Open In TikTok:
Region: SA
Saturday 17 October 2026 00:46:29 GMT
8473
353
14
89

Music

Download

No Watermark .mp4 (48.95MB) No Watermark(HD) .mp4 (48.95MB) Watermark .mp4 (0MB) Music .mp3

Comments

areejsaif52
وعد اللقيا :
وحياة محبتك انت ملكنا الغالي وعشقنا الابدي
2026-10-18 00:45:24
0
saleem05588
جبر الخواطر :
2026-10-17 06:24:05
0
user4926172146940
احمد السقا :
🥰🥰🥰
2026-10-17 06:07:37
0
samirabdin762
Samir 🇶🇦 :
❤️❤️❤️❤️❤️❤️❤️❤️❤️❤️❤️❤️❤️❤️❤️
2026-10-17 00:59:46
1
osama.abuelgasim7
Osama Abuelgasim :
🥰🥰🥰
2026-10-17 08:53:42
0
7tooo97
7tooo🦋 :
😍😍😍
2026-10-17 22:35:59
0
To see more videos from user @montyhilal7, please go to the Tikwm homepage.

Other Videos
Prompting vs RAG vs Fine-tuning — the question every AI team argues about, answered in one picture. 🧠 Stop asking
Prompting vs RAG vs Fine-tuning — the question every AI team argues about, answered in one picture. 🧠 Stop asking "should I fine-tune?" Ask: is the problem style, facts, or judgment? 1️⃣ Prompting — fixes style. Tell the model how to answer: JSON, concise, this tone. → Use when: the facts are right but the format or tone is wrong. No training data. But the model never learns anything new. 2️⃣ RAG (Retrieval Augmented Generation) — fixes facts. The model still doesn't know it, but it can look it up in your docs. → Use when: facts change often, or live in your private docs. Update the docs, and the answers update the same day. No retraining. 3️⃣ Fine-tuning — fixes judgment. Train on examples until the model makes the call the way your team would. → Use when: the pattern is stable, but no prompt can capture it. Needs good examples, and a retrain every time the pattern changes. 👀 The part nobody says: most "we need to fine-tune" problems are really facts problems. Fine-tuning doesn't keep facts fresh, and when your pricing changes next week, the model won't know. Rule: style = prompt, facts = RAG, judgment = fine-tune. Try them in that order. Where teams go wrong: spending weeks building a training set to teach the model their product docs, when RAG would have shipped in days and stayed current. Send this to whoever just said "let's fine-tune it". 📸 Screenshot the last frame — the whole decision in one line. Save it before your next "should we fine-tune?" meeting. Follow @hackproduct — we turn scary AI-engineering concepts into things you can actually ship. ⚡ . . #AIengineering #machinelearning #softwareengineering #LLM #RAG
Kalem 🥲
Kalem 🥲
Man switched up soo quickly once he saw those charges.#fypシ゚viral #TrueCrime #funny #policeofficer #officersoftiktok
Man switched up soo quickly once he saw those charges.#fypシ゚viral #TrueCrime #funny #policeofficer #officersoftiktok




About

Legal