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model fine-tuning

67 articles · Page 1 of 1
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
Jun 17, 2026 · Artificial Intelligence

How OmniVideo-100K Generates High‑Quality Audio‑Video Training Data for Better Multimodal Understanding

The article analyzes why existing audio‑video QA pipelines break narrative continuity, proposes a structured‑script and evidence‑chain approach to automatically build the OmniVideo-100K dataset of 100K high‑quality QA pairs, and shows that fine‑tuning open‑source multimodal models on this data yields consistent accuracy gains across multiple benchmarks.

OmniVideo-100Kaudio-video datasetbenchmark evaluation
0 likes · 12 min read
How OmniVideo-100K Generates High‑Quality Audio‑Video Training Data for Better Multimodal Understanding
DataFunSummit
DataFunSummit
Jun 13, 2026 · Artificial Intelligence

Beyond General LLMs: Efficient Adaptation and Data Value Mining for Finance

The article details a systematic practice—starting from the “iceberg” challenges of finance, through data and knowledge engineering, reverse knowledge extraction with REER, multi‑dimensional synthetic data generation, prompt engineering (APO), cost‑aware fine‑tuning, inference acceleration, and emotion‑value evaluation—culminating in actionable guidelines for deploying large models in banking scenarios.

Knowledge EngineeringLarge Language Modelsemotion evaluation
0 likes · 14 min read
Beyond General LLMs: Efficient Adaptation and Data Value Mining for Finance
Smart Workplace Lab
Smart Workplace Lab
May 29, 2026 · Artificial Intelligence

Who Owns AI‑Generated Assets? A Three‑Step Protocol for Tracing Company Data Contributions

After a team fine‑tuned a customer‑service model with internal complaint data, the article shows why AI‑driven data quickly becomes unaccountable, then presents a three‑step protocol—weight table, automatic log generation, and commercial‑benefit mapping—to transparently trace contributions and prevent ghost‑labor disputes.

AI GovernanceAI data provenanceWorkflow Automation
0 likes · 6 min read
Who Owns AI‑Generated Assets? A Three‑Step Protocol for Tracing Company Data Contributions
Weekly Large Model Application
Weekly Large Model Application
May 5, 2026 · Artificial Intelligence

Task Alignment: How to Give Your Speech Model a Job Handbook

The article explains how to transform a pretrained speech model into a product‑ready assistant by defining demonstration data, clarifying team debates on persona, safety, and length, contrasting alignment with pretraining, and highlighting common pitfalls to avoid during deployment.

Dialogue SystemsSafetydata annotation
0 likes · 6 min read
Task Alignment: How to Give Your Speech Model a Job Handbook
Old Zhang's AI Learning
Old Zhang's AI Learning
Apr 13, 2026 · Artificial Intelligence

Fine‑Tune Any Large Model on Apple Silicon with mlx‑tune

The article introduces mlx‑tune, a community project that wraps the MLX library with Unsloth's API to enable local fine‑tuning of large language, vision, TTS, STT, OCR, and embedding models on Apple Silicon Macs, outlines its workflow from prototype to cloud, provides installation steps, code examples, and discusses its capabilities and limitations.

Apple SiliconLarge Language ModelsMultimodal
0 likes · 9 min read
Fine‑Tune Any Large Model on Apple Silicon with mlx‑tune
AgentGuide
AgentGuide
Mar 18, 2026 · Artificial Intelligence

From Beginner to Senior AI Agent Engineer: A Proven Learning Path

The article outlines a step‑by‑step learning roadmap for AI Agent development, covering large‑model fundamentals, prompt engineering, retrieval‑augmented generation, agent architecture, production practices, and fine‑tuning concepts to help engineers progress from entry‑level to senior roles.

AI AgentPrompt engineeringRAG
0 likes · 9 min read
From Beginner to Senior AI Agent Engineer: A Proven Learning Path
Data Party THU
Data Party THU
Feb 25, 2026 · Artificial Intelligence

Why Multimodal LLMs Miss Tiny Objects—and How to Fix It

This article analyzes why multimodal large language models often fail to detect small objects, identifies three core bottlenecks, and presents a four‑tiered optimization roadmap—from zero‑cost inference tricks to data augmentation, model fine‑tuning, and engineering safeguards—backed by three real‑world case studies and actionable guidelines.

Inference Optimizationdata augmentationmodel fine-tuning
0 likes · 20 min read
Why Multimodal LLMs Miss Tiny Objects—and How to Fix It
Amazon Cloud Developers
Amazon Cloud Developers
Jan 22, 2026 · Artificial Intelligence

How Amazon’s New Bedrock and SageMaker Features Cut AI Agent Costs and Speed Up Customization

The article explains how Amazon Bedrock’s reinforced fine‑tuning and SageMaker AI’s new serverless model‑customization dramatically lower the cost and latency of AI agents, delivering up to a 73% accuracy boost and shrinking model‑building cycles from months to days for enterprises of any size.

AI AgentAmazon BedrockAmazon SageMaker
0 likes · 9 min read
How Amazon’s New Bedrock and SageMaker Features Cut AI Agent Costs and Speed Up Customization
Amap Tech
Amap Tech
Jan 8, 2026 · Artificial Intelligence

How AI Powers Fancy Video Generation for Real‑World POI Scenes

This article details the AI techniques behind Gaode's "Street Ranking" project, explaining the Fancy video concept, the dual training and production pipelines, and the use of SFT, reinforcement learning, MoE‑LoRA, distribution‑matching distillation, and quality‑filtering to achieve 25× faster generation with high aesthetic fidelity.

AI video generationDistillationMultimodal
0 likes · 24 min read
How AI Powers Fancy Video Generation for Real‑World POI Scenes
PMTalk Product Manager Community
PMTalk Product Manager Community
Nov 25, 2025 · Product Management

Avoid the 3 Common AI Product Management Pitfalls: Prompt Engineering, RAG, and Fine‑Tuning

The article examines why AI product managers repeatedly fall into three traps—over‑relying on prompt engineering, blindly adopting Retrieval‑Augmented Generation, or costly fine‑tuning—by presenting real‑world failures, debunking myths, and offering a five‑layer decision framework with cost, data, resource, and risk analysis to choose the right solution.

AI product managementPrompt engineeringRAG
0 likes · 24 min read
Avoid the 3 Common AI Product Management Pitfalls: Prompt Engineering, RAG, and Fine‑Tuning
DataFunTalk
DataFunTalk
Oct 22, 2025 · Artificial Intelligence

How Large Language Models Power Xiaomi’s Xiao AI Assistant

This article explains how Xiaomi’s Xiao AI assistant leverages large language models for intent routing, domain‑specific intent understanding, and response generation, detailing the system architecture, challenges such as knowledge requirements and latency constraints, and the shift from prompt engineering to model fine‑tuning.

AI assistantIntent RoutingLarge Language Models
0 likes · 5 min read
How Large Language Models Power Xiaomi’s Xiao AI Assistant
DataFunTalk
DataFunTalk
Oct 10, 2025 · Artificial Intelligence

How Large Language Models Power Xiaomi’s Xiao AI Assistant

This article explains how large language models are integrated into Xiaomi’s Xiao AI assistant, covering intent distribution, domain‑specific intent understanding, response generation, architectural design, challenges such as knowledge requirements and latency, and the shift from prompt engineering to model fine‑tuning.

AI assistantIntent RoutingLarge Language Models
0 likes · 5 min read
How Large Language Models Power Xiaomi’s Xiao AI Assistant
DataFunSummit
DataFunSummit
Oct 5, 2025 · Artificial Intelligence

How Xiaomi’s XiaoAI Harnesses Large Models for Intent Routing and Response Generation

This article explains how Xiaomi’s XiaoAI assistant integrates large language models for intent distribution, vertical intent understanding, and response generation, detailing the architecture, challenges such as knowledge requirements and sub‑200 ms latency, and the shift from prompt engineering to model fine‑tuning that boosted user retention by 10% and query satisfaction by 8%.

AI assistantArtificial IntelligenceIntent Routing
0 likes · 4 min read
How Xiaomi’s XiaoAI Harnesses Large Models for Intent Routing and Response Generation
DataFunSummit
DataFunSummit
Sep 29, 2025 · Artificial Intelligence

How Large Language Models Power XiaoAI: From Intent Routing to Response Generation

This article explores how large language models are integrated into Xiaomi’s XiaoAI assistant, detailing the system’s architecture, intent distribution, domain-specific understanding, and response generation, while sharing practical challenges, prompt engineering solutions, and fine‑tuning strategies that boosted user retention and query satisfaction.

AI assistantsIntent RoutingLarge Language Models
0 likes · 4 min read
How Large Language Models Power XiaoAI: From Intent Routing to Response Generation
Architects Research Society
Architects Research Society
Sep 12, 2025 · Artificial Intelligence

Master Generative AI: From Core Concepts to Advanced Techniques

This comprehensive guide walks you through generative AI fundamentals—including transformers, diffusion models, large language models, and multimodal systems—then explores practical API usage with OpenAI, Hugging Face, and Vertex AI, followed by model fine‑tuning, LoRA, knowledge injection, and advanced topics such as model distillation, prompt chaining, AutoML, tool integration, and retrieval‑augmented generation.

AutoMLPrompt engineeringmodel fine-tuning
0 likes · 3 min read
Master Generative AI: From Core Concepts to Advanced Techniques
Amazon Cloud Developers
Amazon Cloud Developers
Sep 12, 2025 · Artificial Intelligence

Fine‑Tune Amazon Nova Canvas in 12 Hours for Consistent, Cohesive AI Storyboards (Part 2)

This guide shows how to fine‑tune the Amazon Nova Canvas foundation model on Amazon Bedrock using a 12‑hour workflow that extracts character frames from video with Amazon Rekognition, prepares labeled data, configures hyper‑parameters, creates a custom model, deploys it with provisioned throughput, and tests the model to generate coherent storyboard images, while also covering cleanup steps to avoid ongoing costs.

AI storyboardAmazon BedrockAmazon Nova Canvas
0 likes · 17 min read
Fine‑Tune Amazon Nova Canvas in 12 Hours for Consistent, Cohesive AI Storyboards (Part 2)
Amap Tech
Amap Tech
Aug 7, 2025 · Artificial Intelligence

Boosting Codebase Upgrades with Code RAG and Agent‑Driven Fine‑Tuning

This article describes how the Gaode terminal team tackled large‑scale repository upgrades by building a code‑RAG and code‑Agent tool, addressing recall and stability issues, then fine‑tuning a small LLM (Qwen3‑4B) with LoRA and custom datasets to achieve reliable, low‑cost, on‑device code‑query performance.

LLMLoRAcode RAG
0 likes · 11 min read
Boosting Codebase Upgrades with Code RAG and Agent‑Driven Fine‑Tuning
Zhihu Tech Column
Zhihu Tech Column
Jul 25, 2025 · Artificial Intelligence

Boost Creative Writing with Zhi-Create-Qwen3-32B: Training, Eval & Deployment

This article introduces the open‑source Zhi‑Create‑Qwen3‑32B model, detailing its fine‑tuned training on creative‑writing data, the multi‑domain dataset strategy, curriculum‑learning based SFT, evaluation on WritingBench, and practical deployment options across various hardware and inference frameworks.

DeploymentEvaluationcreative writing
0 likes · 11 min read
Boost Creative Writing with Zhi-Create-Qwen3-32B: Training, Eval & Deployment
Sohu Tech Products
Sohu Tech Products
Jul 23, 2025 · Artificial Intelligence

Boosting Video Moderation with Multimodal CLIP and Efficient Vector Search

This article describes how a video review system combines multimodal CLIP models, image‑text feature alignment, and optimized vector‑search databases such as RedisSearch and Elasticsearch to detect prohibited content in real time and perform large‑scale historical recall, while addressing challenges of generalization, storage cost, and inference speed.

AICLIPmodel fine-tuning
0 likes · 18 min read
Boosting Video Moderation with Multimodal CLIP and Efficient Vector Search
ITPUB
ITPUB
Jul 7, 2025 · Operations

How to Build a DeepSeek AI Ops Platform: Architecture & Implementation

This article presents a comprehensive blueprint for constructing a DeepSeek-powered AI Ops platform, detailing the six‑module architecture, data collection stack, AI engine deployment options, application and interaction layers, implementation road‑map, model training, security measures, cost estimates, and risk mitigation strategies.

AI OpsDeepSeekOperations Automation
0 likes · 8 min read
How to Build a DeepSeek AI Ops Platform: Architecture & Implementation
DataFunSummit
DataFunSummit
Jun 19, 2025 · Artificial Intelligence

How Large Models Are Revolutionizing Douyin’s User Experience – Expert Insights

In a detailed interview, ByteDance AI specialist Cai Conghuai explains how large‑model techniques such as SFT, DPO and RAG address Douyin’s multimodal user‑experience challenges, improve signal detection, root‑cause analysis, and outline future AI‑agent breakthroughs for content platforms.

AI AlgorithmsEvaluationMultimodal Learning
0 likes · 11 min read
How Large Models Are Revolutionizing Douyin’s User Experience – Expert Insights
AI Frontier Lectures
AI Frontier Lectures
Jun 5, 2025 · Artificial Intelligence

Bridging Thought Leaps: How CoT‑Bridge Boosts LLM Reasoning Accuracy

This paper introduces the Thought Leap Bridge task and the CoT‑Bridge model, which detect and fill missing intermediate steps in chain‑of‑thought reasoning, dramatically improving large language model performance on mathematical and logical benchmarks and enhancing downstream distillation and reinforcement‑learning pipelines.

Chain-of-ThoughtCoT-BridgeLLM
0 likes · 8 min read
Bridging Thought Leaps: How CoT‑Bridge Boosts LLM Reasoning Accuracy
Model Perspective
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.

AILarge Language Modelseducation
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
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 ApplicationsLLMPrompt engineering
0 likes · 31 min read
LLM Application in Text Information Detection and Extraction: A Case Study of Blue-Collar Recruitment Data Processing
Architect
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
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
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Feb 24, 2025 · Artificial Intelligence

Unlock Data+AI Fusion: Fine‑Tune Multimodal Models on DataWorks with GPU‑Ready Notebooks

This tutorial shows how to use Alibaba Cloud DataWorks' serverless GPU resource groups together with the open‑source LLaMA‑Factory framework to fine‑tune the Qwen2‑VL‑2B multimodal model for tourism‑domain Q&A, covering environment setup, dataset preparation, parameter configuration, training, and interactive inference.

DataWorksGPULLaMA-Factory
0 likes · 10 min read
Unlock Data+AI Fusion: Fine‑Tune Multimodal Models on DataWorks with GPU‑Ready Notebooks
DataFunTalk
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.

Knowledge EngineeringLarge Language ModelsRAG
0 likes · 9 min read
Roundtable on Enhancing Large Model Effectiveness: RAG, Tool Use, and Knowledge Engineering
AI2ML AI to Machine Learning
AI2ML AI to Machine Learning
Feb 10, 2025 · Artificial Intelligence

Eight Ways Enterprises Can Leverage DeepSeek

The article outlines eight distinct enterprise strategies for adopting DeepSeek, categorizing them by model maturity, available data types, and specific business challenges, and maps these approaches onto four capability tiers—from basic compliance requirements to advanced multimodal, low‑cost solutions.

AI agentsDeepSeekEnterprise AI
0 likes · 3 min read
Eight Ways Enterprises Can Leverage DeepSeek
Code Mala Tang
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
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 BedrockLLMOpsMLOps
0 likes · 14 min read
Generative AI Applications, MLOps, and LLMOps: A Comprehensive Overview
AsiaInfo Technology: New Tech Exploration
AsiaInfo Technology: New Tech Exploration
Dec 9, 2024 · Artificial Intelligence

How Programming Large Models Transform Repository‑Level Code Completion

This article examines how programming large models combined with code knowledge graphs can overcome the limited context of traditional code‑completion tools, detailing key techniques, trigger strategies, context acquisition methods, model fine‑tuning practices, current challenges, and future research directions for intelligent, repository‑wide code suggestions.

AI programmingLarge Language ModelsSoftware engineering
0 likes · 14 min read
How Programming Large Models Transform Repository‑Level Code Completion
Baobao Algorithm Notes
Baobao Algorithm Notes
Nov 24, 2024 · Artificial Intelligence

How Marco‑o1 Merges Chain‑of‑Thought Fine‑Tuning with Monte‑Carlo Tree Search for Superior Reasoning

The article introduces Marco‑o1, an open‑source LLM that enhances complex reasoning by fine‑tuning on Chain‑of‑Thought data, integrating Monte‑Carlo Tree Search, introducing mini‑step actions and a reflection mechanism, and evaluates its performance on multilingual math and translation benchmarks.

Artificial IntelligenceChain-of-ThoughtLLM
0 likes · 15 min read
How Marco‑o1 Merges Chain‑of‑Thought Fine‑Tuning with Monte‑Carlo Tree Search for Superior Reasoning
Architecture and Beyond
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
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.

Multimodal AIPrompt engineeringe-commerce
0 likes · 10 min read
Multimodal Large Model for Voucher Verification: Prompt Engineering and Fine‑Tuning
Baidu Geek Talk
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
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 CLIPImage-Text MatchingMultimodal AI
0 likes · 16 min read
Multimodal AI-Powered Video Content Moderation System Using Chinese CLIP and Vector Search
DataFunTalk
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.

Enterprise AILarge Language ModelsRLHF
0 likes · 28 min read
Comprehensive Guide to Selecting, Adapting, and Deploying Large Language Models for Enterprise Applications
DataFunTalk
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 developmentEvaluationPrompt engineering
0 likes · 15 min read
Large Model Application Development: Architecture, Lifecycle, and Prompt Engineering
DataFunTalk
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 researchDomain AdaptationLarge Language Models
0 likes · 16 min read
Research on Domain Large Models by Fudan University Knowledge Factory Lab
58 Tech
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
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
Baidu Tech Salon
Baidu Tech Salon
Apr 16, 2024 · Artificial Intelligence

How Baidu’s AI Tools Turn Everyone Into a Developer – Key Takeaways from Li Yanhong’s Speech

In his Create 2024 AI Developer Conference keynote, Li Yanhong outlines Baidu’s latest large‑model series, AI‑native development platforms (AgentBuilder, AppBuilder, ModelBuilder), performance breakthroughs, real‑world case studies, and the strategic vision that makes AI development accessible to all developers and enterprises.

AIIndustry Trendsdeveloper tools
0 likes · 28 min read
How Baidu’s AI Tools Turn Everyone Into a Developer – Key Takeaways from Li Yanhong’s Speech
AI Large Model Application Practice
AI Large Model Application Practice
Apr 10, 2024 · Artificial Intelligence

What Is Self‑RAG? A Simple Guide to Self‑Reflective Retrieval‑Augmented Generation

This article explains the motivation behind Self‑RAG, describes its core workflow—including conditional retrieval, enhanced generation, and self‑evaluation tokens—details the four evaluation metrics (Retrieve, IsRel, IsSup, IsUse), and provides a Python scoring example using log‑probabilities.

Evaluation MetricsLLMLogprobs
0 likes · 13 min read
What Is Self‑RAG? A Simple Guide to Self‑Reflective Retrieval‑Augmented Generation
DataFunSummit
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 Modelsmodel fine-tuning
0 likes · 12 min read
Knowledge Map for Large Model Application Development
Baidu Geek Talk
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 QianfanLarge Model Platform
0 likes · 12 min read
Qianfan Large Model Platform: Making Large Models Accessible - Baidu's Latest Work on Model Fine-tuning and Deployment
phodal
phodal
Dec 25, 2023 · Artificial Intelligence

Can AI Write Perfect Unit Tests? Inside AutoDev’s Prompt‑Fine‑Tune Pipeline

This article explains how the open‑source AutoDev plugin builds an end‑to‑end AI‑assisted coding solution that fine‑tunes open LLMs, constructs a Unit Eval dataset, engineers prompts for unit‑test generation, and enforces quality through a unified write‑evaluate pipeline.

AIJavaSpring
0 likes · 9 min read
Can AI Write Perfect Unit Tests? Inside AutoDev’s Prompt‑Fine‑Tune Pipeline
DataFunTalk
DataFunTalk
Dec 19, 2023 · Artificial Intelligence

Enterprise Large‑Model Deployment and Data Governance: Insights from Deepexi’s President

The article examines how enterprises can adopt domain‑specific large models by balancing demand‑side cost‑reduction needs with supply‑side mature training techniques, discusses team composition, fine‑tuning methods, data governance for unstructured data, and outlines Deepexi’s product ecosystem designed to improve efficiency, performance, and user experience.

AI DeploymentEnterprise AILarge Language Models
0 likes · 13 min read
Enterprise Large‑Model Deployment and Data Governance: Insights from Deepexi’s President
DataFunSummit
DataFunSummit
Dec 16, 2023 · Artificial Intelligence

Enterprise Large Model Deployment: Data Governance, Fine‑Tuning Strategies, and Cost Economics

The article examines how enterprises can adopt domain‑specific large models by addressing talent and cost challenges, outlining self‑supervised pre‑training, instruction fine‑tuning, data governance for unstructured data, dataset balance, model‑type selection, and integrated product solutions to achieve efficient, high‑performance AI deployments.

AI DeploymentData GovernanceEnterprise AI
0 likes · 13 min read
Enterprise Large Model Deployment: Data Governance, Fine‑Tuning Strategies, and Cost Economics
DataFunSummit
DataFunSummit
Dec 13, 2023 · Artificial Intelligence

Enterprise Large‑Model Deployment: Data Governance, Fine‑Tuning Strategies, and Cost Economics

The article explores how enterprises can adopt domain‑specific large language models by addressing talent and cost challenges, outlining training pipelines, data governance for unstructured data, dataset balancing, fine‑tuning techniques, and a product ecosystem that lowers deployment barriers while optimizing performance and economics.

AI DeploymentData Governancecost economics
0 likes · 13 min read
Enterprise Large‑Model Deployment: Data Governance, Fine‑Tuning Strategies, and Cost Economics
DataFunTalk
DataFunTalk
Aug 19, 2023 · Artificial Intelligence

Applying Large Language Models to Zhihu's Bridge Platform: Use Cases, Challenges, and Solutions

This article details how Zhihu's internal Bridge platform integrates large language models for business analysis, knowledge taxonomy, natural‑language‑to‑filter conversion, and ad‑hoc data queries, describing the workflow, technical hurdles, iterative improvements, and future directions.

AI for business analyticsLarge Language ModelsPrompt engineering
0 likes · 12 min read
Applying Large Language Models to Zhihu's Bridge Platform: Use Cases, Challenges, and Solutions
Tencent Cloud Developer
Tencent Cloud Developer
Aug 14, 2023 · Artificial Intelligence

Overview of Open‑Source Large Language Models: Llama 2, ChatGLM 2, Usage, Fine‑Tuning and Comparison

The article reviews the rapid evolution of open‑source large language models, detailing Meta’s Llama 2 series and Tsinghua’s ChatGLM 2, their enhanced capabilities such as RLHF, larger context windows, safety‑usefulness trade‑offs, performance gains, download and fine‑tuning procedures, and how they increasingly rival proprietary models like GPT‑4.

AIChatGLM2Llama2
0 likes · 10 min read
Overview of Open‑Source Large Language Models: Llama 2, ChatGLM 2, Usage, Fine‑Tuning and Comparison
Baidu Intelligent Cloud Tech Hub
Baidu Intelligent Cloud Tech Hub
Aug 8, 2023 · Artificial Intelligence

Unlocking LMOps: How Enterprises Can Master Large Model Operations

This article explains the evolution from traditional machine learning to the current large‑model era, introduces LMOps concepts and key technologies, compares them with MLOps, and showcases Baidu Cloud's Qianfan platform as a practical solution for building, deploying, and managing large language models in industry.

AI OperationsBaidu CloudLMOps
0 likes · 22 min read
Unlocking LMOps: How Enterprises Can Master Large Model Operations
DeWu Technology
DeWu Technology
Jul 5, 2023 · Artificial Intelligence

Fine-tuning Large Language Models with LoRA/QLoRA and Deploying via GPTQ Quantization on KubeAI

The article explains how LoRA and its 4‑bit QLoRA extension dramatically reduce trainable parameters and GPU memory for fine‑tuning large language models, while GPTQ post‑training quantization compresses weights for cheap inference, and shows how KubeAI integrates these techniques into a one‑click workflow for 7 B, 13 B, and 33 B models from data upload to API deployment.

GPTQKubeAILarge Language Models
0 likes · 13 min read
Fine-tuning Large Language Models with LoRA/QLoRA and Deploying via GPTQ Quantization on KubeAI
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
May 26, 2023 · Artificial Intelligence

Unlock High‑Quality Chinese Image Generation with PAI‑Diffusion: New Features & Fine‑Tuning Guide

This article introduces the upgraded PAI‑Diffusion Chinese models, highlighting major improvements in image quality and style diversity, detailing lightweight fine‑tuning methods such as LoRA and Textual Inversion, showcasing controllable editing, scenario‑specific customization, and providing step‑by‑step usage instructions on popular platforms.

AILoRATextual Inversion
0 likes · 14 min read
Unlock High‑Quality Chinese Image Generation with PAI‑Diffusion: New Features & Fine‑Tuning Guide
DataFunSummit
DataFunSummit
May 23, 2023 · Artificial Intelligence

Continuous Semantic Enhancement for Neural Machine Translation: Methodology, Experiments, and Community Deployment

This article introduces a continuous semantic enhancement approach for neural machine translation that overcomes the limitations of discrete data‑augmentation techniques, details the neighbor risk minimization training objective, presents benchmark improvements on ACL‑2022 datasets, and describes practical deployment and fine‑tuning workflows in the Modu community.

Neural Machine Translationcontinuous semantic augmentationcontrastive learning
0 likes · 19 min read
Continuous Semantic Enhancement for Neural Machine Translation: Methodology, Experiments, and Community Deployment
Architect
Architect
Apr 24, 2023 · Artificial Intelligence

MOSS 003: Open‑Source Large Language Model Development, Training Data, and Plugin‑Enabled Deployment

The article details the evolution of the open‑source MOSS series—from OpenChat 001 to MOSS 003—covering data collection, fine‑tuning procedures, multilingual capabilities, plugin architecture, example code for inference, and upcoming releases, providing a comprehensive technical overview for AI practitioners.

AIMOSSPlugins
0 likes · 11 min read
MOSS 003: Open‑Source Large Language Model Development, Training Data, and Plugin‑Enabled Deployment