6 ways to reduce hallucination using prompt engineering
🚀 Unlocking the Power of Prompt Engineering: Reduce Hallucination and Boost LLM Model Performance! 🤖✨
A new course launched for interview preparation
We have launched a new course “Interview Questions and Answers on Large Language Models (LLMs)” series.
This program is designed to bridge the job gap in the global AI industry. It includes 100+ questions and answers from top companies like FAANG and Fortune 500 & 100+ self-assessment questions.
The course offers regular updates, self-assessment questions, community support, and a comprehensive curriculum covering everything from Prompt Engineering and basics of LLM to Supervised Fine-Tuning (SFT) LLM, Deployment, Hallucination, Evaluation, and Agents etc.
Detailed curriculum (Get 50% off using coupon code MED50 for first 10 users)
Free self assessment on LLM (30 MCQs in 30 mins)
There’s a hidden gem that few know about, the art of crafting prompts to elicit precise, reliable results. And today, I’m excited to share an important trick that can make all the difference in your LLM interactions.
🔑 Here’s how to master prompt engineering like a pro:
1️⃣ Include Instructions
2️⃣ Repetition Matters
3️⃣ Strategic Positioning
4️⃣ Temperature Control
5️⃣ Restrict Output
6️⃣ Add COT-Style Instructions
To dive deeper into this topic, I invite you to watch the video at the following link:
🔗 Connect with us:
YouTube — @MasteringLLM
Medium — Mastering LLM (Large Language Model)
LinkedIn — https://www.linkedin.com/company/mastering-llm-large-language-model
