model fine-tuning

DataFunSummit

May 27, 2025 · Artificial Intelligence

Integrating Data and AI for Platform Engineering: IDP Practices, Model Fine‑Tuning, and R&D Efficiency at Qunhe Technology

The article details how Qunhe Technology combines big data and AI within an Internal Developer Product (IDP) framework to boost software development efficiency, outlines architectural decisions, presents fine‑tuning pipelines for code‑review models, and shares interview insights from senior technical director Dr. Hu Guanghuan on practical implementations and ROI.

AIData EngineeringR&D efficiency

0 likes · 22 min read

Integrating Data and AI for Platform Engineering: IDP Practices, Model Fine‑Tuning, and R&D Efficiency at Qunhe Technology

Model Perspective

Apr 8, 2025 · Artificial Intelligence

Why Learning Machine Learning Still Matters in the Age of Giant AI Models

The article argues that despite the rapid rise of powerful large language models, mastering machine learning remains essential because it underpins these models, offers customized solutions for specialized tasks, and cultivates the mathematical, programming, and analytical skills needed to effectively use and extend AI technologies.

AIEducationLarge Language Models

0 likes · 10 min read

Why Learning Machine Learning Still Matters in the Age of Giant AI Models

Beijing SF i-TECH City Technology Team

Apr 7, 2025 · Artificial Intelligence

LLM Application in Text Information Detection and Extraction: A Case Study of Blue-Collar Recruitment Data Processing

This article explores the application of Large Language Models (LLM) in text information detection and extraction, focusing on blue-collar recruitment data processing. It details the implementation of LLM through prompt engineering, RAG enhancement, and model fine-tuning to improve data cleaning efficiency and accuracy.

AI applicationsLLMNatural Language Processing

0 likes · 31 min read

LLM Application in Text Information Detection and Extraction: A Case Study of Blue-Collar Recruitment Data Processing

Architect

Apr 1, 2025 · Artificial Intelligence

When to Fine‑Tune Large Language Models vs. Relying on Prompting and RAG

The article explains why most projects should start with prompt engineering or simple agent workflows, outlines the scenarios where model fine‑tuning adds real value, compares fine‑tuning with Retrieval‑Augmented Generation, and offers practical criteria for deciding which approach to adopt.

AI deploymentLarge Language ModelsLoRA

0 likes · 9 min read

When to Fine‑Tune Large Language Models vs. Relying on Prompting and RAG

DataFunSummit

Feb 25, 2025 · Artificial Intelligence

Collecting High-Quality LLM Training Data and Custom Model Training Guide

This article explains what constitutes high‑quality LLM training data, why large datasets are essential, outlines the step‑by‑step process for collecting, preprocessing, and fine‑tuning models, and highlights the best data sources—including web content, books, code repositories, and news—while noting available free datasets.

AILLMWeb Scraping

0 likes · 9 min read

Collecting High-Quality LLM Training Data and Custom Model Training Guide

DataFunTalk

Feb 11, 2025 · Artificial Intelligence

Roundtable on Enhancing Large Model Effectiveness: RAG, Tool Use, and Knowledge Engineering

Experts from Dipu, Ant Financial, iKang, and Zhihu discuss practical strategies for improving large model performance, covering RAG, tool‑using, offline knowledge engineering, multimodal training, evaluation metrics, and future trends, while sharing case studies from manufacturing, healthcare, retail, and C‑end applications.

AI evaluationLarge Language ModelsRAG

0 likes · 9 min read

Roundtable on Enhancing Large Model Effectiveness: RAG, Tool Use, and Knowledge Engineering

Code Mala Tang

Feb 2, 2025 · Artificial Intelligence

How to Deploy DeepSeek AI Coding Assistant Locally: A Step‑by‑Step Guide

This guide walks you through the hardware and software prerequisites, Docker-based installation, environment configuration, model fine‑tuning, IDE integration, maintenance, and troubleshooting for running the DeepSeek AI programming assistant entirely on your own machine.

AI coding assistantDeepSeekDocker

0 likes · 12 min read

How to Deploy DeepSeek AI Coding Assistant Locally: A Step‑by‑Step Guide

DataFunSummit

Jan 11, 2025 · Artificial Intelligence

Generative AI Applications, MLOps, and LLMOps: A Comprehensive Overview

This article presents a detailed overview of generative AI lifecycle management, covering practical use cases such as email summarization, the roles of providers, fine‑tuners and consumers, MLOps/LLMOps processes, retrieval‑augmented generation, efficient fine‑tuning methods like PEFT, and Amazon Bedrock services for model deployment and monitoring.

Amazon BedrockLLMOpsPEFT

0 likes · 14 min read

Generative AI Applications, MLOps, and LLMOps: A Comprehensive Overview

Architecture and Beyond

Nov 23, 2024 · Artificial Intelligence

A Comprehensive Overview of AIGC Engineering Architecture and Its Core Roles

This article examines the AIGC engineering architecture, detailing its data, model, fine‑tuning, inference, application, and monitoring layers, and explains the distinct responsibilities and challenges of application engineers, algorithm engineers, and “alchemy” specialists, highlighting how this structured approach accelerates generative AI productization.

AI deploymentAIGCEngineering Architecture

0 likes · 24 min read

A Comprehensive Overview of AIGC Engineering Architecture and Its Core Roles

DaTaobao Tech

Nov 1, 2024 · Artificial Intelligence

Multimodal Large Model for Voucher Verification: Prompt Engineering and Fine‑Tuning

By leveraging multimodal large models such as GPT‑4o and fine‑tuned Qwen‑VL, the study builds a prompt‑engineered and SFT‑enhanced voucher verification system that classifies product categories, detects diverse defects, and estimates problem counts, achieving up to 90 % accuracy and meeting real‑time business throughput requirements.

e-commercemodel fine-tuningmultimodal AI

0 likes · 10 min read

Multimodal Large Model for Voucher Verification: Prompt Engineering and Fine‑Tuning

Baidu Geek Talk

Oct 23, 2024 · Artificial Intelligence

Integrating Yuan 2.0 Large Model with PaddleNLP: Overview, Usage Steps, and Interaction Examples

The open‑source Yuan 2.0 large model is fully integrated into Baidu’s PaddleNLP, offering quick inference for tasks like code generation, translation, and reasoning, along with efficient distributed training and fine‑tuning features such as Zero Padding optimization, enabling developers to easily deploy and customize the model via simple setup steps and example interactions.

AIJavaLLM

0 likes · 10 min read

Integrating Yuan 2.0 Large Model with PaddleNLP: Overview, Usage Steps, and Interaction Examples

Sohu Tech Products

Sep 25, 2024 · Artificial Intelligence

Multimodal AI-Powered Video Content Moderation System Using Chinese CLIP and Vector Search

The article describes a multimodal AI video moderation system built on Alibaba’s Chinese‑CLIP model and hybrid RedisSearch/ElasticSearch vector databases, enabling real‑time violation detection and historical recall, with fine‑tuned black‑market ad detection, FP16 quantization, and OpenVINO acceleration to boost speed and cut storage.

Chinese CLIPElasticsearchOpenVINO optimization

0 likes · 16 min read

Multimodal AI-Powered Video Content Moderation System Using Chinese CLIP and Vector Search

DataFunTalk

Sep 23, 2024 · Artificial Intelligence

Comprehensive Guide to Selecting, Adapting, and Deploying Large Language Models for Enterprise Applications

This article provides an in‑depth, step‑by‑step guide on how enterprises can choose between open‑source and closed‑source large language models, adapt them through incremental pre‑training, instruction fine‑tuning, and reinforcement learning, and finally deploy them across front‑office, middle‑office, and back‑office scenarios to drive digital transformation.

Large Language ModelsRLHFRetrieval-Augmented Generation

0 likes · 28 min read

Comprehensive Guide to Selecting, Adapting, and Deploying Large Language Models for Enterprise Applications

DataFunTalk

Jul 7, 2024 · Artificial Intelligence

Large Model Application Development: Architecture, Lifecycle, and Prompt Engineering

This article presents a comprehensive knowledge map for developing large‑model applications, covering a four‑layer technical architecture, the full development lifecycle, core elements such as prompt engineering and model fine‑tuning, evaluation methods, and practical case studies, offering guidance for both enterprises and startups.

AI Application Developmentevaluationlarge model

0 likes · 15 min read

Large Model Application Development: Architecture, Lifecycle, and Prompt Engineering

DataFunTalk

Jun 15, 2024 · Artificial Intelligence

Research on Domain Large Models by Fudan University Knowledge Factory Lab

This article presents Fudan University's Knowledge Factory Lab research on domain large models, covering background, challenges, data selection, source‑enhanced tagging, capability improvements, self‑correction, collaborative workflows, and retrieval‑augmented generation for practical AI deployment.

AI researchLarge Language ModelsRetrieval-Augmented Generation

0 likes · 16 min read

Research on Domain Large Models by Fudan University Knowledge Factory Lab

58 Tech

Jun 3, 2024 · Artificial Intelligence

Parameter-Efficient Fine-Tuning (PEFT) Methods for Large Language Models: LoRA, QLoRA, AdaLoRA, SoRA, and Training Acceleration with Unsloth

This article systematically analyzes popular parameter‑efficient fine‑tuning (PEFT) techniques for large language models—including Adapter Tuning, Prefix Tuning, LoRA, QLoRA, AdaLoRA, and SoRA—detailing their principles, implementation code, experimental results on NLU tasks, and practical acceleration using the Unsloth library.

AdaLoRALarge Language ModelsLoRA

0 likes · 39 min read

Parameter-Efficient Fine-Tuning (PEFT) Methods for Large Language Models: LoRA, QLoRA, AdaLoRA, SoRA, and Training Acceleration with Unsloth

Sohu Tech Products

Apr 24, 2024 · Artificial Intelligence

Domain-Specific Large Model Construction Guide

The guide explains why generic LLMs struggle with enterprise tasks and outlines two remedies—retrieval‑augmented generation and domain‑specific fine‑tuning—detailing dataset creation, training strategies (full‑parameter, LoRA, Q‑LoRA), validation methods, hardware benchmarks, and practical tips such as supervised fine‑tuning, 30% domain data, and a stepwise tuning pipeline.

AIdataset constructiondomain-specific LLM

0 likes · 16 min read

Domain-Specific Large Model Construction Guide

DataFunSummit

Apr 9, 2024 · Artificial Intelligence

Knowledge Map for Large Model Application Development

This article outlines a comprehensive knowledge map for building large‑model applications, detailing a four‑layer technical architecture, development lifecycle, core elements such as prompt engineering and fine‑tuning, evaluation methods, and real‑world case studies across various AI use cases.

AI Application DevelopmentLarge Language Modelsevaluation

0 likes · 12 min read

Knowledge Map for Large Model Application Development

DataFunTalk

Mar 13, 2024 · Artificial Intelligence

Exploring and Practicing Large Models at Ctrip

This presentation by Ctrip algorithm expert Wei Peng details the rapid development of large language models, their core capabilities, and practical applications in the travel industry, covering content marketing, multimodal interactions, customer service efficiency, model comparisons, fine‑tuning, and inference performance optimization.

AI applicationsLarge Language ModelsTravel Industry

0 likes · 3 min read

Exploring and Practicing Large Models at Ctrip

Baidu Geek Talk

Jan 15, 2024 · Artificial Intelligence

Qianfan Large Model Platform: Making Large Models Accessible - Baidu's Latest Work on Model Fine-tuning and Deployment

Baidu’s Qianfan Large Model Platform provides a one‑stop enterprise solution with 54 pre‑installed models, advanced fine‑tuning, comprehensive evaluation metrics, and optimized deployment that cuts costs up to 90% and boosts throughput 3‑5×, enabling rapid, affordable AI application development.

AI Native ApplicationsBaidu QianfanCost Optimization

0 likes · 12 min read

Qianfan Large Model Platform: Making Large Models Accessible - Baidu's Latest Work on Model Fine-tuning and Deployment