#parameter-efficient fine-tuning
186 related articles
·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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·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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Industry Insights·2 min
AI Product Development in Practice: Model Selection, Building Moats, and Paths to Commercialization
Practical strategies for AI product development: why not to train models from scratch, when to use APIs vs. fine-tuning, building product moats, and the full path from evaluation systems to commercialization.
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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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Expert Opinions·3 min
The Salary Ceiling for Agent Engineers: Two Critical Dividing Lines
Agent engineer salary gaps hinge on two dividing lines: real production deployment experience and depth of foundational theory including deep learning, fine-tuning, and reinforcement learning.
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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·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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Tutorials·2 min
Java + AI: A Practical Path for Programmers to Break Through the Age-35 Career Crisis
How Java programmers can break through the age-35 career bottleneck by stacking AI skills. Covers AI learning levels, Java+AI synergy, and actionable transition strategies.
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Product Reviews·3 min
8K Stars on GitHub: Deep Dive into the Most Comprehensive LLM Resource Repository
Deep analysis of the awesome-LLM-resources project (8200+ GitHub Stars), covering multimodal AI, Agents, MCP protocol, model training, o1 reasoning, SLMs, and more for LLM practitioners.
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Deep Dives·5 min
Hugging Face Transformers: A Comprehensive Guide to the 160K-Star Open-Source AI Framework
Comprehensive guide to Hugging Face Transformers, the 160K-star GitHub framework—covering architecture, multimodal support, quantization, and inference optimization for loading, fine-tuning, and deploying pre-trained models.
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Product Reviews·4 min
Hugging Face Transformers: Deep Dive into the 160K-Star Open Source AI Model Framework
Deep dive into Hugging Face Transformers: architecture, multimodal support, ecosystem, and trends. Learn how this 160K-Star project became essential for AI developers.
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Product Reviews·3 min
VS Code AI Toolkit 2.0 Deep Dive: Agent Builder + Free Access to GPT-5
Deep dive into VS Code AI Toolkit 2.0 major update, covering Agent Builder, MCP tool integration, batch testing, model evaluation, and a complete guide to using GPT-5 and Claude for free via GitHub Models.
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Tutorials·4 min
2025 LLM Career Transition Roadmap: A Three-Phase Plan from Foundations → Frameworks → Real-World Projects
A systematic 2025 LLM career transition roadmap covering Python, Transformers, LangChain, LlamaIndex, RAG, Agent development, and fine-tuning across three phases achievable in 2-3 months.
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Product Reviews·3 min
awesome-LLM-resources: A Comprehensive Analysis of the 8,200-Star LLM Learning Resource Repository on GitHub
In-depth analysis of the 8,200-star GitHub project awesome-LLM-resources, covering multimodal generation, Agents, model training, MCP protocol, and more — a one-stop LLM learning guide.
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