#parameter-efficient fine-tuning
14 related articles
·2 min
Getting Started with LLM Fine-Tuning: Teaching AI New Tricks with Your Own Data
A detailed guide to LLM fine-tuning: core concepts, three key characteristics, and when to use it. Learn how to train a specialized AI model with small, high-quality datasets, plus comparisons with RAG and prompt engineering.
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·3 min
Prompt Template Design for Document Summarization: A Practical Guide to Three-Layer Progressive Prompt Engineering
A practical guide to three-layer progressive Prompt template design for document summarization, covering requirements analysis, architecture design, validation, and optimization — boosting information extraction completeness from 78% to 91%.
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Stable Diffusion Local Deployment Guid…
·2 min
Stable Diffusion Local Deployment Guide: Free Unlimited AI Image Generation
Complete guide to deploying Stable Diffusion locally for free unlimited AI image generation. Covers installation steps, model management, hardware requirements, and use cases.
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AI Large Language Model Learning Roadm…
·4 min
AI Large Language Model Learning Roadmap: A Complete Guide from Zero to Project Implementation
A systematic AI LLM learning roadmap covering prompt engineering, RAG, AI Agent development, and fine-tuning — with beginner-friendly paths and practical tips.
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Tutorials·3 min
Agent Tuning: A Complete Guide to Training LLMs with Agent Capabilities
A deep dive into Agent Tuning principles and practices, covering why Agent training is needed, the evolution from Prompt to RAG to Agent, development workflows, and cost assessment for private deployment.
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Tutorials·3 min
MCP Protocol Explained: Differences from Function Calling and Agent Tool Development in Practice
Deep dive into MCP (Model Context Protocol): its principles, communication architecture, and practical applications. Compare MCP vs Function Calling, explore client-server communication and security.
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Industry Insights·3 min
The Survival Crisis and Transformation Path for Traditional Programmers in the AI Coding Wave
Since 2025, AI-driven tech layoffs intensify with 75% of coding work coverable by AI. This article analyzes programmers' structural elimination crisis and the transformation path from code workers to AI architects.
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Industry Insights·4 min
In-Depth Analysis of the AI Large Model Job Market: Two Core Directions and Future Trends
In-depth analysis of the AI large model job market, breaking down the two core directions—algorithm research and engineering deployment—covering requirements, barriers, and career prospects.
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Research·3 min
MementoGUI: A Multimodal Memory Management Framework for Solving Long-Horizon GUI Agent Amnesia
MementoGUI is a plugin-style multimodal memory management framework that solves GUI agent forgetting in long-horizon tasks through dual time-scale memory and four memory control operators, boosting long-task completion without fine-tuning.
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Tutorials·3 min
Can You Really Transition to AI/LLM in Three Months? A Deep Dive into the Learning Roadmap
Deep dive into a popular 3-month AI/LLM transition roadmap: from Python basics and Prompt engineering to LangChain, RAG, Agents, and hands-on projects, with realistic time estimates and pitfall warnings.
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Industry Insights
Deep Dive into Three Major LLM Career …
·3 min
Deep Dive into Three Major LLM Career Paths: Requirements, Tech Stacks, and Career Prospects
Deep analysis of three core LLM roles—Application Engineer, Development Engineer, and Algorithm Engineer—covering technical requirements, salary thresholds, and career prospects including RAG, fine-tuning, and inference deployment.
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Product Reviews·2 min
Kimi K2.6 Open-Source Hands-On: How Strong Is Its Orchestration of 300 Concurrent Agents?
Deep analysis of Moonshot AI's open-source Kimi K2.6 Agent orchestration: 300 sub-Agents executing 4000-step tasks, outperforming GPT-5.4 in coding benchmarks, LoRA fine-tuning on 2x RTX 4090s.
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Tutorials·3 min
Learning LLM Application Development from Scratch: A Complete Roadmap from RAG to Agent
How to start LLM application development from scratch? A complete roadmap covering Python basics, RAG knowledge bases, and Agent development with LangChain.
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Product Reviews·3 min
ChuanhuChatGPT: A Comprehensive Analysis of the 15K-Star Open-Source Multi-Model Chat Interface
Deep dive into ChuanhuChatGPT, a 15K-star open-source project with multi-model access, Agent support, RAG file Q&A, GPT fine-tuning, and web search.
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