#QLoRA

126 related articles

Jul 28, 2026·3 min

A Beginner's Guide to AI Agents: Two Learning Paths for Developers and Practitioners

How to learn AI Agents from scratch? This guide covers two clear paths: developers go from Python to LLMs to open-source framework source code; practitioners use Claude Code or similar tools to get results fast.

Jul 27, 2026·3 min

From RAG to Agent Tuning: A Complete Guide to Deploying LLM Agents

A deep dive into LLM Agent frameworks covering RAG, Agent core components (tools, memory, planning), and Agent Tuning workflows with cost considerations for production deployment.

Jul 27, 2026·3 min

Jensen Huang's First Tweet Backs AI Open Source — But It's Really About NVIDIA's Ecosystem Anxiety

Jensen Huang's first tweet backs AI open source, but behind it lies NVIDIA's deep anxiety over CUDA ecosystem displacement. We analyze why open-source models matter and what's really at stake.

Jul 27, 2026·3 min

DeepSeek-OCR Deployment & Fine-Tuning in Practice: From vLLM Inference to Unsloth Fine-Tuning

Complete guide to DeepSeek-OCR from vLLM inference deployment and Unsloth model loading to fine-tuning, covering cloud server setup, GPU selection, and code examples — all on a single 4090 GPU.

Jul 26, 2026·3 min

DeepSeek-OCR Deployment and Fine-Tuning: A Complete Hands-On Guide

Master the full DeepSeek-OCR deployment and fine-tuning workflow: vLLM inference deployment, efficient Unsloth fine-tuning, dataset preprocessing, LoRA training, validation, and RAG vector database integration.

Jul 25, 2026·3 min

Jensen Huang Backs Chinese Open-Source AI: Great Models Deserve to Be Widely Used

NVIDIA CEO Jensen Huang says US companies should absolutely be allowed to use Chinese open-source AI models like DeepSeek and Kimi, calling backdoor fears a misunderstanding and arguing great models drive more compute demand.

Jul 23, 2026·6 min

Hands-On with Qwen 3.8 Max: How an Open-Source Model Closes In on Top-Tier Closed Models

Qwen 3.8 Max has 2.4 trillion parameters and will be open-sourced. In KingBench testing it scored 81.25%, ranking second, beating Claude Opus 4.8 and trailing only Fable 5. A deep dive into its performance across 8 tests.

Jul 21, 2026·3 min

Frontend Developers Transitioning to AI: A Complete Three-Phase Minimalist Roadmap

A structured 3-phase roadmap for frontend developers transitioning to AI: master Transformer fundamentals, build RAG & Agent skills, then advance to model fine-tuning.

Jul 21, 2026·2 min

Qwen3 Fine-Tuning in Practice: A Complete Guide to Local Deployment and Domain Training

A hands-on guide to LLM fine-tuning: from understanding model weights to local Qwen3 deployment, dataset preparation, and domain-specific training. Build a complete AI engineering skill set.

Jul 20, 2026·2 min

OpenSpiel 2.0 Released: Reinforcement Learning Framework Fully Embraces Large Language Models

OpenSpiel 2.0 by Google DeepMind adds LLM fine-tuning examples, MCP tool server, JSON trajectories, AlphaZero on JAX, 19 new games, and Windows support.

The Wild Juxtaposition of AI's Evoluti…

Jul 20, 2026·2 min

The Wild Juxtaposition of AI's Evolution: What Has Technology Crossed From Start to Now?

A "How it started vs. How it's going" comparison reveals generative AI's stunning leap. We explore the key drivers—compute, data, algorithms, and open source—plus the real challenges ahead.

Jul 17, 2026·3 min

AI Large Language Models for Beginners: Core Concepts and Chinese Model Landscape

New to AI? This guide clarifies AI, machine learning, deep learning, and LLMs, traces milestones from Deep Blue to DeepSeek, and maps out China's LLM landscape.

Jul 16, 2026·3 min

Complete Practical Guide to LLM Fine-Tuning: A Roadmap for Beginners

A practical LLM fine-tuning roadmap for beginners — covering when to fine-tune, LoRA/QLoRA selection, data prep, tools like Unsloth, and evaluation for Llama, Mistral, and Gemma.

Jul 15, 2026·3 min

The Complete LLM Learning Roadmap: From Beginner to Expert — Courses and Resources Recommended

Confused by scattered LLM resources and unclear learning paths? This guide maps a complete roadmap from basics to advanced, covering Karpathy, Stanford CS224N, DeepLearning.AI, Hugging Face, plus RAG, fine-tuning, and Agent deep dives.

Jul 15, 2026·2 min

GPT-5.6 Launch Triggers Industry Chain Reactions: The New Competition Landscape of Compute, Energy, and Open Source

GPT-5.6 raises frontier model expectations, Anthropic extends Fable 5; data center power bottlenecks emerge; open-source GLM5.2 rivals top closed models; AI review burden overlooked.

Jul 14, 2026·2 min

Learning AI Large Language Models from Scratch: A Complete Roadmap That Avoids the Three Biggest Mistakes

90% of AI beginners struggle with large language models due to misdirection, poor Prompt logic, and lack of real-world deployment skills. This guide covers the complete learning path from zero to practice.

Jul 12, 2026·3 min

How Machine Learning Engineers Can Adapt in the AI Era: A Guide to Skill Trade-offs and Career Reinvention

In the AI wave, ML engineers' work is quietly shifting: from building models to using them, from feature engineering to LLM app development. This article outlines the new skills to prioritize, fading old ones, and how to turn AI into career leverage.

Jul 12, 2026·7 min

Breaking Down the Core Skills of an AI Application Engineer: From Beginner to Industrial-Grade Deployment

Knowing how to call an API doesn't make you an AI engineer. This article breaks down the complete skill structure of an AI application engineer, covering Python fundamentals, LLM fine-tuning, Agent development, and enterprise projects.

Jul 12, 2026·5 min

Advanced Machine Learning Reading List: How to Choose the Right Book Among These 4 Classics?

Torn between Géron, Chollet, and Raschka? This article breaks down 4 classic ML books for self-learners aiming at finetuning and small language models (SLM), helping you find the best advanced path.

Jul 12, 2026·4 min

ChatGLM Large Model Development Tutorial: From Zero to Enterprise Deployment

Systematically learn ChatGLM large model development, covering Transformer principles, RAG, private deployment, fine-tuning, and Agent development, with a roadmap and hands-on cases.