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Mmatthewtruong81matthew-codes.hashnode.dev3d ago · 6 min read

RAG or Fine-Tuning? An AI Development Services Comparison

Quick answer: RAG (Retrieval-Augmented Generation) enables the language model to retrieve the most up-to-date information directly from the live knowledge base at query time without retraining. Fine-t

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ASAdi Shikopeningthehood.hashnode.dev4d ago · 8 min read

APIs Were the First Layer. Training Is the Next One

We all see the world changing. A few years ago, AI was not really accessible to most builders. The important research existed long before ChatGPT, including the 2017 paper Attention Is All You Need, w

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NSNeeloppher Syedneeloppher.hashnode.devMay 30 · 5 min read

Fine-Tuning Qwen2.5-0.5B to Write SRE Post-Mortem Summaries

Writing post-mortem root-cause summaries is time-consuming and inconsistent. Junior SREs miss contributing factors. Senior SREs write summaries that vary in depth and structure. Zero-shot LLMs produce

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HAHarsh Agaleharshagale.hashnode.devMay 22 · 5 min read

How I Fine-Tuned Llama 2 Using QLoRA on Free GPU Resources

Training and fine-tuning Large Language Models (LLMs) is often considered expensive and hardware-intensive. Most tutorials online assume access to powerful GPUs with large amounts of VRAM, which can b

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AKAbijah Kajabikablog.abijah.meMay 9 · 9 min read

Teaching a Small LLM to Design Electronic Circuits: Fine-Tuning Qwen3-4B on 100K KiCad Netlists

How I built a 100K-example dataset of executable circuit netlists and fine-tuned a 4B parameter model that scores 88% on functional circuit generation, rivaling GPT-4o's published benchmarks. The Pro

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SRStephane Royflexai.hashnode.devMay 8 · 15 min read

How to Use EasyR1 for Reinforcement Learning on FlexAI

EasyR1 is a reinforcement learning fine-tuning framework that supports GRPO, DAPO, and REINFORCE for reasoning-focused post-training. Use it when SFT starts plateauing on tasks like math, code, or log

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HHemaNhema-sdet.hashnode.devApr 29 · 4 min read

Fine‑Tuning Isn’t Optional: How QA Engineers Make AI Models Production‑Ready

As part of my daily learning journey in AI, today I focused on fine‑tuning foundation models and quickly realized something important: Most AI models fail not because they are weak — but because they

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RSRahul Sehrawatai-zero-to-hero.hashnode.devApr 12 · 11 min read

Finetune vs Prompt vs Retrieve — When to Use What

Here is the single most common mistake I see teams make when they start building with LLMs. Someone says "the model doesn't know about our stuff." A smart-sounding engineer nods and says "we should fine-tune it on our data." A project gets scoped. A ...

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RSRahul Sehrawatai-zero-to-hero.hashnode.devApr 12 · 11 min read

Pretraining, Finetuning, RLHF — The Three-Act Training Story

Here is a question you have probably never thought to ask. When you talk to ChatGPT or Claude, and the thing on the other end is unfailingly polite, stays on task, refuses things that seem dangerous, and generally behaves like an assistant — where di...

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Iiniyarajaniniyarajanhashnodedev.hashnode.devMar 30 · 6 min read

RAG vs Fine-Tuning: When to Use Each AI Strategy

Last week, we were building an AI agent to answer questions about our company's internal documentation. The team split into two camps: one pushing for fine-tuning GPT-4 on our docs, the other advocating for a RAG system. Sound familiar? We see this d...

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#finetuning

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#finetuning

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Trending tags this week

RAG or Fine-Tuning? An AI Development Services Comparison

APIs Were the First Layer. Training Is the Next One

Fine-Tuning Qwen2.5-0.5B to Write SRE Post-Mortem Summaries

How I Fine-Tuned Llama 2 Using QLoRA on Free GPU Resources

Teaching a Small LLM to Design Electronic Circuits: Fine-Tuning Qwen3-4B on 100K KiCad Netlists

How to Use EasyR1 for Reinforcement Learning on FlexAI

Fine‑Tuning Isn’t Optional: How QA Engineers Make AI Models Production‑Ready

Finetune vs Prompt vs Retrieve — When to Use What

Pretraining, Finetuning, RLHF — The Three-Act Training Story

RAG vs Fine-Tuning: When to Use Each AI Strategy