#model fine-tuning
36 related articles
Tutorials·3 min
AnythingLLM Installation & Configuration Guide: Building a Local Knowledge Base with API Integration
Complete guide to AnythingLLM local knowledge base setup: installation tips, Ollama model configuration, document vectorization, recall optimization, and API integration.
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Tutorials·1 min
AI Agent Learning Roadmap: A Complete Guide from LLM Fundamentals to Enterprise-Level Project Implementation
A systematic AI Agent learning roadmap covering Python setup, Prompt Engineering, RAG, LangChain, multi-Agent collaboration, with enterprise medical consultation system case study and phased learning plan.
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Tutorials·3 min
Complete Learning Roadmap for Java Developers Transitioning to AI Engineering
A detailed five-phase learning roadmap for Java developers transitioning to AI engineering, covering Spring AI, LangChain4j, RAG core technology, and Agent development.
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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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Deep Dives·4 min
Core Principles of the Transformer Architecture: A Deep Dive into Self-Attention Mechanisms and Engineering Optimizations
Deep dive into Transformer architecture covering self-attention QKV mechanics, Encoder-Decoder structure, Flash Attention memory optimization, RoPE positional encoding, and GQA inference acceleration.
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Tutorials·4 min
Complete Guide to Building a Local AI Knowledge Base with Qwen3.5 + RAGFlow + Ollama
Complete guide to building a local AI knowledge base with Qwen3.5, RAGFlow, and Ollama, covering Docker deployment, Embedding model configuration, knowledge base creation, and RAG system setup.
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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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Tutorials·2 min
Learning AI Large Language Models from Scratch: A Guide to Learning Paths, Hardware, and Programming Languages
A beginner's guide to learning AI large language models — covering learning paths, hardware requirements, Python essentials, and cloud services for learners at every level.
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Product Reviews·3 min
Cursor 3.0 Deep Dive: From Code Editor to AI Agent Command Center
Deep dive into Cursor 3.0's major upgrades: proprietary Composer 2 coding model, multi-agent parallel workflows, built-in browser and design mode. Exploring the shift from VS Code fork to Rust rewrite and the AI agent programming paradigm.
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Tutorials·2 min
Career Progression in AI/LLM Application Development: Four Stages from Beginner to 40K Monthly Salary
A systematic four-stage career path for AI/LLM application development: from RAG and Agent fundamentals to architecture design, helping developers transition to AI roles targeting 40K+ monthly salary.
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Tutorials·2 min
npcpy: An Open-Source Framework That Rethinks AI Agent Development with Software Engineering Principles
Deep dive into npcpy's four-layer architecture, multi-agent collaboration, knowledge graph lifecycle management, and deployment strategies for building stable, controllable AI Agent systems.
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Tutorials·3 min
RAG Technology Full-Stack Analysis: Core Principles, Enterprise Implementation & Learning Path
Deep analysis of RAG technology's core principles, three key values, enterprise implementation cases, common pitfalls, and a systematic learning roadmap covering vector databases, retrieval optimization, and Knowledge Graph fusion.
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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
Frontend to AI Full-Stack: Complete Sk…
·2 min
Frontend to AI Full-Stack: Complete Skill Tree & Learning Roadmap
A complete skill tree for frontend developers transitioning to AI full-stack engineers, covering TypeScript, NestJS, LangChain JS, RAG, vector databases, and Tauri 2 with a clear learning roadmap.
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Tutorials
LLM Learning Roadmap: A Complete Guide…
·3 min
LLM Learning Roadmap: A Complete Guide from Beginner to Project Implementation Across Seven Core Modules
A systematic breakdown of seven core LLM learning modules covering environment setup, Prompt Engineering, RAG, Agents, dev frameworks, fine-tuning, and hands-on projects for developers.
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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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