Generate Consistent LLM Output - Are we all prompting wrong??? (Part 1)

preview_player
Показать описание
A MUST SEE for anyone performing fact-based queries with LLMs. Why do LLMs provide inconsistent outputs to fact-based queries? Explore how different temperature and sampling settings affect the output of LLMs. Part 1 of 2.

How do configuration settings impact the output of LLMs and your workflow?

Learn how to use temperature and sampling settings for different use cases and how each can be set to provide more consistent output, particularly in fact-based workflows.

Please subscribe for more content.

Join our discord community:

  1. llmware
Рекомендации по теме
Generate Consistent LLM 0:11:09

Generate Consistent LLM Output - Are we all prompting wrong??? (Part 1)

Generate Consistent LLM 0:09:28

Generate Consistent LLM Output - Are we all prompting WRONG??? (Part 2)

NEW Challenge for 0:16:52

NEW Challenge for LLM: CONSISTENCY ALIGNMENT

Controlling LLM outputs 0:11:40

Controlling LLM outputs for practical applications

Evaluating the Output 0:01:42

Evaluating the Output of Your LLM (Large Language Models): Insights from Microsoft & LangChain

Gemini LLM JSON 0:16:47

Gemini LLM JSON Mode: Generate Structured Output from LLM

Using LangChain Output 0:23:04

Using LangChain Output Parsers to get what you want out of LLMs

How to use 0:08:25

How to use Self-Consistency to boost LLM performance

Meta AI just 0:19:02

Meta AI just tried to recreate OpenAI o1 - Self improving thinking AI

Better patching using 0:06:38

Better patching using LLM prompting, via Self-Consistency - ArXiv:2306.00108

NEX by Nurix 0:05:50

NEX by Nurix - Episode 7 | Ensuring Consistency in LLM-Powered Systems

Evaluating LLMs using 0:11:25

Evaluating LLMs using Langchain

A Guide to 0:21:29

A Guide to JSON output with LLM prompts

What is Prompt 0:08:33

What is Prompt Tuning?

Master the Perfect 0:08:30

Master the Perfect ChatGPT Prompt Formula (in just 8 minutes)!

Make AutoGen Consistent: 0:28:58

Make AutoGen Consistent: CONTROL your LLM agents for ACCURATE Postgres AI Data Analytics

Better patching using 0:07:24

Better patching using LLM prompting, via Self-Consistency - ArXiv:2306.00108

Instructor - Structured 0:10:44

Instructor - Structured LLM Outputs - Hands on Demo

LLM Evaluation Basics: 0:05:18

LLM Evaluation Basics: Datasets & Metrics

Ep 6. Conquer 0:07:23

Ep 6. Conquer LLM Hallucinations with an Evaluation Framework

Tutorial #5: Strict 0:28:30

Tutorial #5: Strict JSON LLM Framework - Get LLM to output JSON exactly the way you want it!

'I want Llama3 0:24:02

'I want Llama3 to perform 10x with my private knowledge' - Local Agentic RAG w/ llama3

How to pick 0:00:52

How to pick the best LLM

LLM Module 4: 0:31:11

LLM Module 4: Fine-tuning and Evaluating LLMs | 4.13.2 Notebook Demo Part 2