LLMs - Labellerr

LLMs

A collection of 28 posts

5 Best Tools for LLM Fine-Tuning

Finding the right tools to fine-tune Large Language Models (LLMs) can be a daunting task, especially with the growing number of options in 2024. If you’ve tried customizing an LLM for your specific needs, you already know the struggle: compatibility issues, high costs, and complex setups can turn a

9 Key Differences between GPT4 and Llama2 you should know

9 Key Differences Between GPT4 & Llama2 One Should Know

GPT-4 and Llama 2 are advanced AI models with unique strengths. GPT-4, known for high creativity and multimodal support, excels in complex tasks but requires extensive resources. Llama 2, open-source and multilingual, is more efficient and accessible, ideal for broader user engagement.

Comparing top large language models for multiple uses

Top Large Language Models for Writers, Developers, and Marketers: A Comprehensive Comparison

Explore the best LLM with real-time data capabilities. Compare GPT-4, BARD, and other LLMs based on performance, multilingual support, and applications.

Illustration of data and other matrices

Data Collection and Preprocessing for Large Language Models

Are you struggling to harness the full potential of Large Language Models (LLMs) due to the complexities of data collection and preprocessing? You're not alone. Many developers and researchers face significant challenges in sourcing and preparing the vast amounts of text data necessary for training these advanced AI

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: Aligning Large Language Models with Human Preferences

DPO vs PPO: How To Align LLM

Direct Preference Optimization (DPO) and Proximal Policy Optimization (PPO) are two approaches to align Large Language Models with human preferences. DPO focuses on human feedback to optimize models directly, while PPO uses reinforcement learning for iterative improvements.

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

WebVoyager, an AI web agent, autonomously interacts with websites using multimodal models like GPT-4. It handles complex tasks, blending text, image, and context data for applications in e-commerce, customer support, and more, redefining online interactions.

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 with AIDE for Enhanced AV Perception

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

Evaluating Large Language Models: A Comprehensive Guide

Evaluating Large Language Models: A Comprehensive Guide

Evaluating large language models (LLMs) requires multidimensional strategies to assess coherence, accuracy, and fluency. Explore key benchmarks, metrics, and methods to ensure LLM reliability, transparency, and performance in real-world applications.

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

Devin AI, by Cognition Labs, is a groundbreaking autonomous AI designed to work alongside developers. It automates coding tasks, handles projects from start to finish, and empowers developers to focus on strategic challenges, transforming software development.

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

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

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

Enhancing LLM Data Annotation with Few-Shot Chain of Thought

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

Claude 3.5 vs Claude 2 vs ChatGPT Comparison

Claude 3.5 Vs Claude 2 Vs ChatGPT: A Detailed Comparison

A few months ago, we published a blog, “Llama 2 Vs GPT-3.5 Vs GPT-4” to help you choose the best tool for your needs. Since then, the generative AI landscape has continued to evolve. * OpenAI’s ChatGPT rolled out new voice and image capabilities * OpenAI is testing a new

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

Llama 2, GPT-3.5, and GPT-4 offer unique AI capabilities: Llama 2 is cost-effective and adaptable, GPT-3.5 handles complex queries for larger businesses, and GPT-4 excels in high-level tasks needing minimal human input.

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

Large Language Models (LLMs) are reshaping fields from computational biology and code generation to creative arts, healthcare, robotics, and synthetic data generation, offering innovative solutions beyond common applications like chatbots.

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