Zero-shot, One-shot and Few-shot Prompting Explained | Prompt Engineering 101

Показать описание

👉Large Language Models are a very powerful tool. And to elicit desired information from LLMs, effective prompts are a must. And that's what Prompt Engineering is.
👉Three prompting engineering techniques: zero-shot, one-shot and few-shot prompting will improve your prompting skills.

👉Zero-shot is most basic form of prompting. It simply shows the model a prompt without examples.
👉One-shot prompting is when you show the model a single example.
👉Few-shot prompting involves providing a few labeled examples in the prompt.
--------------------------------------------------------
Generative AI Learning Roadmaps 🔥
--------------------------------------------------------

--------------------------------------------------------------
Enroll in the BlackBelt Plus Program 🔥
--------------------------------------------------------------
👉 Become a Data Scientist without leaving your job
👉 1️⃣ Hands-on 50+ Industry Projects,
👉 2️⃣ 1:1 Mentorship Sessions, and
👉 3️⃣ Dedicated Interview Preparation along with Placement Support

--------------------------------------------------------------

Check out these Blogs to know more-

-------------------------------------------
🔥 Important Video Links
-------------------------------------------

--------------------------------------------------------------
Free Certification Courses 🔥
--------------------------------------------------------------

Рекомендации по теме

Комментарии

Book FREE 1:1 Mentorship for Gen AI / Data Science

Analyticsvidhya

thanks for sharing! short and to the point

elvenkim

You should indicate that the example you give for zero-shot prompting is not exactly zero-shot in the strict sense because LLMs are trained with the raw capability of predicting the next word given previous words. From LLM to GPT, there is already low-shot prompt tuning for question answering. Similarly, you can tune an LLM into sentence completion, story generation, dialogue generation, or even audio/image generation, etc. (other purposes).

XuancongWang

Hi, may i check with you where do you get the figures in timestamp 2:56? Thank you!

jingkailim

how is example (shot) given to model is taken into consideration at run time.. not able to understand.

arpitsisodia

I heard if you use few shot prompting with a bunch of bad data you can make the AI say some illegal stuff.

Krebzonide

Zero-shot, One-shot and Few-shot Prompting Explained | Prompt Engineering 101

Zero-shot, One-shot and Few-shot Prompting Explained | Prompt Engineering 101

Prompt Engineering 101: Zero-shot, One-shot, and Few-shot prompting

ChatGPT Prompt Engineering: Zero, One and Few Shot Prompting

Mit Beispielen ChatGPT verbessern: Few-Shot vs Zero-Shot Prompting | Tutorial #06

Prompt Engineering 101: Autocomplete, Zero-shot, One-shot, and Few-shot prompting

What is Zero-Shot Learning?

Zero, One, and Few Shot Prompting with Langchain and OpenAI LLMs

What is Zero shot, One shot and few shot prompting in ChatGPT #tutorial

ECCV 2024 Redux: Day 1 - Robust Calibration of Large Vision-Language Adapters

Large Language Models Are Zero Shot Reasoners

ChatGPT Prompt Engineering: Zero-Shot, Few-Shot, and Chain of Thoughts

Prompt Engineering: Zero-shot, One-shot, Few-shot Techniques Explained (Practical Implementation)

Few Shot Learning - EXPLAINED!

Few-Shot Prompting Explained

Zero, One, and Few Shot Prompting | ChatGPT Complete Guide: Learn Midjourney, ChatGPT 4 & More

Provide an example of all three methods of Zero Shot, One-shot and Few-shot Prompting

🚀 Zero Shot, One Shot and Few Shot Prompting | Generative AI Course - Part 5 | Prompt Engineering

Understanding Zero-shot, One-shot, and Few-shot Prompting

Prompt Engineering 101 I Zero Shot, One Shot, and Few Shot Prompting #8

Engineer the Future of AI: Zero, One, and Few-Shot Prompts

One Prompt, Two Prompt, One Shot, Few Shot

Como funciona a técnica Few-Shot Prompting (na prática!) | Inteligência Artificial

Zero-Shot, One-Shot, Few-Shot, dan lainnya

Prompt Engineering Tutorial – Master ChatGPT and LLM Responses