#LoRA troubleshooting
37 related articles
·2 min
Claude Code Product Development Workflow: From Ad-Hoc Q&A to Systematic Collaboration
Explore how to systematically integrate Claude Code into product development workflows, covering context management, task decomposition, prompt templates, review loops, and team collaboration standards.
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·3 min
AI Model Selection Guide: Pre-trained, Fine-tuned, or Trained from Scratch?
How to choose between pre-trained models, fine-tuning, and training from scratch for new AI projects. A systematic decision framework covering problem definition, data assessment, and cost trade-offs.
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·3 min
Calibra v0.7.1: A Detailed Guide to Pre-Training Data Integrity Detection for Robot Learning
Calibra v0.7.1 introduces an integrity workflow to detect timestamp anomalies, motion jitter, camera defects, and incomplete episodes in robot learning data before training, supporting LeRobot, HDF5, and robomimic formats.
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·3 min
Dex: Turn Your AI Coding Assistant into an Analytics Engineer with One Command
Dex by Exmergo adds analytics engineering skills to Claude Code, Cursor & other AI assistants via one command, with read-only schema mapping, cost guardrails, and drift detection.
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·3 min
2x, Not 10x: The Real Productivity Gains from Programming with LLMs
The 10x AI programming productivity myth debunked. Learn why 2x is the realistic gain from LLM-assisted coding, why generation outpaces verification, and practical tips for developers and teams.
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·4 min
Mass-Producing AI Short Dramas in Practice: Building a Continuous Production Workflow with Skills
The hardest part of AI short dramas isn't generating a pretty shot, but keeping characters, scenes, and style consistent. This article uses a real American campus drama test to detail how to build reusable workflows with Skills, plus three pitfall-avoidance tips.
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·4 min
NRF52840 Bluetooth Keyboard Development: Hardware Selection and AI-Assisted Project Setup
Building an NRF52840 Bluetooth left-hand keyboard from scratch: why NRF52840+ZMK, AI-assisted project init, pin assignment, and real-world debugging of Bootloader offsets and Kconfig configuration.
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·3 min
Can Small Local Models Become Software Domain Experts? A RAG Architecture Deep Dive
Can small local models (1.5B–3B) become software domain experts? This article breaks down CPT, SFT, RAG, and Agent architectures, with a layered RAG-centric design for CPU-only local deployment.
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·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.
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·3 min
Building a Claude Code Skill from Scratch: Let AI Auto-Generate Daily News Reports
A detailed guide on building a custom Claude Code Skill to auto-fetch, filter, and generate daily AI news reports—covering execution logic, task decomposition, HTML visualization, and source tracing.
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·6 min
A Deep Dive into AI Agent Harnesses: The Core Engineering Behind Agent Frameworks
What is an AI Agent's harness? This article systematically dissects the core components of agent frameworks: context management, tool use, control loops, and caching strategies—revealing why the same model performs so differently across harnesses.
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·3 min
Reward Shaping and RL Debugging in Practice: A Systematic Guide from Oscillation to Convergence
Using an FPV drone RL project as a case study, this guide covers reward shaping principles, Bang-Bang control hacking, module isolation, single-variable debugging, and behavior visualization to solve common RL training issues.
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·5 min
Real-World Comparison of 6 Open-Source LLMs for On-Premise Deployment: A Selection Guide to Avoid Pitfalls
A hands-on comparison of 6 open-source LLMs (DeepSeek, Qwen3, Zhipu GLM, Kimi K2, MiniMax M3, Tencent Hunyuan 3) for on-premise deployment—covering hardware cost, inference efficiency, and deployment difficulty.
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·6 min
What Is an FDE? Decoding the Most Sought-After Hybrid Engineer in the AI Deployment Era
FDE (Forward Deployed Engineer) is the hottest emerging role in the AI deployment wave, combining a technical CTO, full-stack AI engineer, and business consultant. Learn the two FDE tracks, core skills, and how to transition into one.
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·7 min
The Agent Engineer Transition Roadmap: A Deep Dive into Three Core Skill Systems
Want to become an Agent engineer? This article systematically covers three core skill tracks—LLM fundamentals, LangChain architecture development, and enterprise deployment—to help you avoid detours.
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·7 min
Why Does WhatsApp Drain So Much Battery? A Deep Dive into the Technical Causes and a Power-Saving Guide
An in-depth analysis of the core technical reasons behind WhatsApp's battery drain—covering persistent connection heartbeats, background tasks, media processing, E2E encryption, and iOS/Android differences—plus 4 practical power-saving tips.
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·2 min
Unsloth v0.1.461-beta: Fix for Local GGUF Vision Model Loading
Unsloth v0.1.461-beta fixes local GGUF vision model loading on llama-server in Studio, adds variant directory companion file lookup for stable multimodal deployment.
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·6 min
Semi-AI Mode: A Practical Guide to Implementing API Automation Testing
Can't make pure AI work? This guide explores the Semi-AI approach to API automation testing, covering key challenges, enterprise framework design, and how AI and frameworks work together for maximum impact.
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·6 min
Vibecoding in Practice: Architecture Trade-offs and Implementation of a Dual-Engine TTS Router
Alibaba Cloud vs Volcano Engine TTS: why "I want both" is the mature engineering decision. Dual-engine routing design, priority trap debugging, and vibecoding-powered implementation.
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·3 min
What Is an AI Agent? The Core Leap from "Talking" to "Doing"
What sets AI Agents apart from chatbots? Explore the four core capabilities—goal understanding, task decomposition, tool calling, and dynamic decision-making—and learn which tasks truly belong to an Agent.
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