LLMs - Labellerr

LLMs

A collection of 28 posts

Meta's Llama 3.1- Is It A Gamechanger For Gen AI?

Meta's Llama 3.1- Is It A Gamechanger For Gen AI?

Table of Contents 1. Introduction 2. Llama 3.1 Model Variants 3. Technical Details of Llama 3.1 4. Performance Evaluation 5. Key Usages of Llama 3.1 6. Llama 3.1 Pricing Comparisons 7. Llama 3.1 vs Other Models: Industry Use Case Comparison 8. Does Llama 3.1

DPO vs PPO: How To Align LLM

DPO vs PPO: How To Align LLM

Large Language Models (LLMs) have rapidly evolved into indispensable tools across various domains. Their ability to process and generate human-like text has opened up new possibilities in fields such as natural language processing, content creation, and customer service. However, with this immense power comes the crucial challenge of alignment. Table

Setting Up Data Processing Pipeline For LLMs With Data-Juicer

Setting Up Data Pipeline For LLMs With Data-Juicer

Table of Contents 1. Introduction 2. How Can Data Be Gathered for LLMs? 3. Ensuring Data Quality 4. Data Processing Pipeline Challenges for LLMs 5. Introducing Data-Juicer 6. Reducing Manual Work with Data-Juicer 7. Conclusion 8. FAQ Introduction In the world of large language models (LLMs), the success lies in

WebVoyager: Autonomously Data Extraction With Multimodal Web Agents

WebVoyager: Autonomously Data Extraction With Multimodal Web Agents

Table of Contents 1. Introduction 2. Fundamentals of Web Agents and Multimodal AI Models 3. Working of WebVoyager Web Agent 4. Implementation Details of WebVoyager Web Agent 5. Evaluation and Error Analysis 6. Difference Between Web Agents and Traditional Web Scraping Tools 7. Applications of Web Agents like WebVoyager in

Evaluating and Finetuning Text To Image Model - Case Study

Evaluating and Finetuning Text To Image Model - Case Study

Table of Contents 1. Introduction 2. Why Evaluate and Fine-Tune These Models 3. How Fine-Tuning is Done for Text-to-Image Models 4. Challenges Faced in Evaluating and Fine-Tuning Text-to-Image Models 5. Case Study: Improving Text-to-Image Models for a Content Creation Client 6. Conclusion 7. FAQ Introduction Text-to-image models are advanced AI

Auto Labeling Using AIDE (Automatic Data Engine)

Vision-language models

AIDE (Automatic Data Engine): Leveraging LLMs To Auto Label

Table of Contents 1. Introduction 2. Introduction To AIDE 3. Components of AIDE 4. Experimental Results of AIDE 5. Conclusion 6. FAQ Introduction The field of autonomous vehicles (AVs) is rapidly evolving, with the promise of revolutionizing transportation by enhancing safety, efficiency, and convenience. Central to the successful deployment of

Evaluating and Fine-Tuning Multimodal Video Captioning Models - A Case Study

Evaluating and Fine-Tuning Multimodal Video Captioning Models - A Case Study

Video captioning models represent a significant advancement in the intersection of computer vision and natural language processing. These models automatically generate textual descriptions for video content, enhancing accessibility, searchability, and user engagement. As video content continues to proliferate across various platforms, the ability to accurately describe and index this content

LLM-Powered Image Caption Generation - Challenges, and Applications

LLM-Powered Image Caption Generation - Challenges, and Applications

Table of Contents 1. Introduction 2. What is Image Captioning Powered by LLMs and How It Works? 3. Applications of LLM-based Image Captioning 4. Challenges and Considerations in LLM-based Image Captioning 5. Labellerr's Multimodal LLM Feature 6. Conclusion 7. FAQS Introduction Image captioning, an intersection of computer vision and natural

Evaluating Large Language Models: A Comprehensive Guide

Evaluating Large Language Models: A Comprehensive Guide

Large language models (LLMs) are transforming how humans communicate with computers. These advanced AI systems can generate human-quality images, and texts, interpret languages, compose various types of creative content, and provide meaningful responses to the questions we ask. But with great power comes great responsibility, which in the context of

Best Voicebot Fine Tuning Tools

Voicebot Fine Tuning

5 Best Voicebot Fine Tuning Tools in 2024

Fine-tuning Language Model Models (LLMs) for voice bots is a pivotal step in optimizing their performance across various voice-based natural language processing tasks. In this incisive examination, we look at five leading tools - Labellerr, Kili, Label Studio, Databricks Lakehouse, and Labelbox - each precisely crafted to meet the specific

Devin AI: The Future Of Coding Or A Teammate For Developers

Devin AI: The Future Of Coding Or A Teammate For Developers

Table of Contents 1. Introduction 2. Origin of Devin AI 3. But what exactly is Devin AI, and how will it change the way we code? 4. How will Devin AI Impact Software Development? 5. Challenges and Considerations 6. Devin AI vs LLMs 7. Devin AI vs Copilot 8. Can

5 Best Tools for LLM Fine-Tuning in 2024

5 Best Tools for LLM Fine-Tuning in 2024

Language Model Model (LLM) fine-tuning tools play a crucial role in optimizing Large Language Models (LLMs) for various natural language processing tasks. In this blog, we'll learn about five leading tools – Labellerr, Kili, Label Studio, Databricks Lakehouse, and Labelbox; each offering unique features and approaches to enhance the fine-tuning process.

2 Best RLHF Libraries in 2024

Best RLHF Libraries in 2024

Imagine you're training a computer to understand and generate human-like language – that's what RLHF helps us do! It's like teaching a computer to get better at talking, writing, and understanding language by giving it feedback. RLHF is important because it helps us make those computer language models even smarter. To

9 Top Tools and Libraries for RLHF in 2024

7 Top Tools for RLHF in 2024

Reinforcement Learning from Human Feedback (RLHF) is a technique used in machine learning, specifically in the training of models to incorporate human input and feedback throughout the learning process. This approach is particularly beneficial for Large Language Models (LLMs) that may be challenging to train using traditional supervised learning methods.

Everything You Need To Know About Vision Language Models (VLMs)

Everything You Need To Know About Vision Language Models (VLMs)

Table of Contents 1. What are Vision Language Models? 2. VLMs vs. LLMs: Distinctive Comparison 3. The Internet's Bias: A Challenge for VLMs 4. What are Domain-specific Large Vision Models (VLMs)? 5. Industry Applications of Domain-Specific Large Vision Models (VLMs) 6. Conclusion 7. Frequently Asked Questions What are Vision Language

Exploring the Game-Changing Potential of Mistral 7B

Table of Contents 1. Introduction 2. Unveiling Mistral 7B: A Compact Powerhouse 3. Mistral 7B's Architecture: Unlocking the Marvels 4. Elevating Benchmarks: Mistral 7B's Outstanding Performance Across Diverse Domains 5. Is Mistral 7B Pioneering Responsible AI Usage? 6. The Accessibility of Mistral 7B and Its Potential 7. Conclusion 8. Frequently

Enhance LLM’s Data Annotation Performance with Few-Shot CoT "Explain-Then-Annotate"

data annotation

How to enhance LLM’s Data Annotation Performance with Few-Shot Chain of Thought Process

Table of Contents 1. Introduction 2. The Power of Labeled Data Augmentation 3. 'Explain-Then-Annotate' Approach 4. How to Enhance Annotation Instructions with GPT-3.5 5. GPT-3.5 as a Zero-shot Data Annotator 6. GPT-3.5 as a Few-shot Data Annotator 7. How to Generate Explanations with GPT-3.5 8. Exploring

Claude2 vs ChatGPT : Reasons why claude 2 better

5 Reasons Why Claude 2 Could Perform Better Than ChatGPT

Introduction to ChatGPT and Claude 2 In the rapidly evolving landscape of artificial intelligence, two standout players have emerged: OpenAI's ChatGPT and Anthropic's Claude 2. Both of these AI chat assistants are designed to engage users with human-like language, providing assistance for a wide range of inquiries and challenges in

9 Key Differences between GPT4 and Llama2 you should know

9 Key Differences Between GPT4 & Llama2 One Should Know

In the rapidly evolving realm of advanced language models, two formidable contenders have risen to prominence, each possessing its own remarkable capabilities and unique strengths. On one side, we have GPT-4, the brainchild of OpenAI, which dazzles with its unprecedented number of parameters and groundbreaking ability to not only process

Llama 2 Vs GPT-3.5 Vs GPT-4: What, When & How To Chose

Llama 2 Vs GPT-3.5 Vs GPT-4: What, When & How To Chose

In today's world, where artificial intelligence is changing how industries work, choosing the right AI model is crucial. Meet Llama 2, GPT-3.5, and GPT-4 – three powerful AI models with unique abilities, ready to help with various projects. In this exploration, we'll go beyond the surface to understand how these

Comparative Analysis of top LLM's

Comparing The Top Large Language Models For Multiple Use Cases

Large Language Models (LLMs) have made AI accessible to individuals without technical expertise, transforming multiple industries. However, with a plethora of LLMs like GPT, LLaMa, Flan-UL2, Bard, and Bloom, choosing the right one can be intimidating. These models excel at language prediction, making them valuable for tasks like content generation

How to choose LLM to suit for use case

How To Chose Perfect LLM For The Problem Statement Before Finetuning

Large Language Models (LLMs) are AI-enabled tools that excel at producing text responses that are human-like when given particular prompts, and they are radically changing how people interact with computers. One of the most well-known LLMs is ChatGPT, which shot to fame in the latter half of 2022. Large Language

Top 6 LLMs Applications No One Is Talking About

6 LLMs Applications No One Is Talking About

A Large language model (LLM) is a form of machine learning model capable of performing various natural language processing (NLP) tasks, including text generation, text classification, conversational question answering, and language translation. The term "large" pertains to the substantial number of values (parameters) that the language model can autonomously adjust

Challenges in LLM Adoption for Enterprises: Introducing LangKit for Secure LLM Adoption

Security Challenges in LLM Adoption for Enterprises And How To Solve Them

In 2023, generative AI gained significant attention, but enterprises are facing challenges in identifying suitable use cases for this technology. Large Language Models (LLMs) have inherent limitations, such as generating irrelevant or off-topic content and being vulnerable to prompt injection, making them a source of concern for businesses. Figure: LLMs

Claude-A better Alternative to ChatGPT and BARD?

Claude-A better Alternative to ChatGPT and BARD?

New developments and advances continue to influence how we communicate with intelligent systems in the always-changing world of conversational AI. As ChatGPT and BARD's era comes to an end, a stunning replacement arises that promises to expand the possibilities for human-like discussions. A new era of seamless and fascinating encounters