--- title: "#finetuning articles | Hashnode" description: "Explore 216 articles tagged #finetuning on Hashnode. Tutorials, guides, and how-tos from the community." url: "https://hashnode.com/tag/finetuning" --- Tag # #finetuning 216 posts · 4 followers [Gayatri Panse](https://hashnode.com/@gradientnotes) · [Oct 31](https://hashnode.com/posts/epoch-2-it-serves-does-it-train/6ae5a81fd7f0b3f843c8bae8) ### [Epoch 2: It Serves. Does It Train?](https://gradientdecent.hashnode.dev/epoch-2-it-serves-does-it-train?utm_source=hashnode&utm_medium=feed) Fine-tuning Gemma 4 with Unsloth on two AMD Radeon RX 7900 XTX cards, and how much of the pain was actually AMD's Slug 34 min read · [gradientdecent.hashnode.dev](https://gradientdecent.hashnode.dev/epoch-2-it-serves-does-it-train?utm_source=hashnode&utm_medium=feed) [Haithem Slimi](https://hashnode.com/@haithem-slimi) · [Oct 30](https://hashnode.com/posts/teaching-a-small-language-model-to-triage-incidents-a-beginner-s-unsloth-and-qlora-tutorial/6ae3e635d6f91c173574e3a9) ### [Teaching a Small Language Model to Triage Incidents: A Beginner’s Unsloth and QLoRA Tutorial](https://nightthoughts.me/teaching-a-small-language-model-to-triage-incidents-a-beginner-s-unsloth-and-qlora-tutorial?utm_source=hashnode&utm_medium=feed) A beginner-friendly Colab + Unsloth experiment in synthetic data, QLoRA, held-out evaluation, and strict schema validation. 31 min read · [nightthoughts.me](https://nightthoughts.me/teaching-a-small-language-model-to-triage-incidents-a-beginner-s-unsloth-and-qlora-tutorial?utm_source=hashnode&utm_medium=feed) [5](https://hashnode.com/posts/teaching-a-small-language-model-to-triage-incidents-a-beginner-s-unsloth-and-qlora-tutorial/6ae3e635d6f91c173574e3a9) [Haithem Slimi](https://hashnode.com/@haithem-slimi) · [Oct 25](https://hashnode.com/posts/teaching-a-small-local-model-to-think-in-differentials/6ade340c34e352aaff851fec) ### [Teaching a Small Local Model to Think in Differentials](https://nightthoughts.me/teaching-a-small-local-model-to-think-in-differentials?utm_source=hashnode&utm_medium=feed) A DDXPlus and QLoRA experiment on Apple Silicon, from held-out evaluation to oMLX deployment 31 min read · [nightthoughts.me](https://nightthoughts.me/teaching-a-small-local-model-to-think-in-differentials?utm_source=hashnode&utm_medium=feed) [Businessware Technologies](https://hashnode.com/@businesswaretech) · [Oct 20](https://hashnode.com/posts/catalog-matching-with-llms-why-changing-knowledge-should-stay-outside-the-model/6ad70080f02cbc56b8a9eab3) ### [Catalog Matching With LLMs: Why Changing Knowledge Should Stay Outside the Model](https://businesswaretech.hashnode.dev/catalog-matching-with-llms-why-changing-knowledge-should-stay-outside-the-model?utm_source=hashnode&utm_medium=feed) Explore how LLMs+RAG improve product catalog matching, incorporate human corrections, and reduce the need for costly model retraining and fine-tuning. 10 min read · [businesswaretech.hashnode.dev](https://businesswaretech.hashnode.dev/catalog-matching-with-llms-why-changing-knowledge-should-stay-outside-the-model?utm_source=hashnode&utm_medium=feed) [1](https://hashnode.com/posts/catalog-matching-with-llms-why-changing-knowledge-should-stay-outside-the-model/6ad70080f02cbc56b8a9eab3) [Taha hussein](https://hashnode.com/@tahahussein) · [Oct 20](https://hashnode.com/posts/fine-tuning-vs-lora-vs-qlora-understanding-efficient-llm-adaptation/6ad7308e25f7cd8d95e2b142) ### [Fine-Tuning vs LoRA vs QLoRA: Understanding Efficient LLM Adaptation](https://tahahussein.hashnode.dev/fine-tuning-vs-lora-vs-qlora-understanding-efficient-llm-adaptation?utm_source=hashnode&utm_medium=feed) Learn how Fine-Tuning, LoRA, QLoRA, and KD-LoRA help customize AI models. Explore key differences, benefits, and LLM adaptation techniques. 5 min read · [tahahussein.hashnode.dev](https://tahahussein.hashnode.dev/fine-tuning-vs-lora-vs-qlora-understanding-efficient-llm-adaptation?utm_source=hashnode&utm_medium=feed) [Muhammad Ariel Shakaramiro](https://hashnode.com/@arielshakaramiro) · [Sep 25](https://hashnode.com/posts/what-does-llm-fine-tuning-actually-learn/6ab685bad8756b66d8d3aa49) ### [What Does Fine-Tuning Actually Learn? Testing QLoRA with Deliberately Controlled Data](https://shaka-ai.hashnode.dev/what-does-llm-fine-tuning-actually-learn?utm_source=hashnode&utm_medium=feed) A controlled QLoRA experiment: format is learned first, facts come later, and brand drift turns out to just be about epoch count. 7 min read · [shaka-ai.hashnode.dev](https://shaka-ai.hashnode.dev/what-does-llm-fine-tuning-actually-learn?utm_source=hashnode&utm_medium=feed) [Muhammad Ariel Shakaramiro](https://hashnode.com/@arielshakaramiro) · [Sep 25](https://hashnode.com/posts/llama3-8b-qlora-finetuning-free-colab/6ab6811de566a637dd49dd06) ### [Fine-Tuning Llama 3.1 8B for Free on Colab: QLoRA, Unsloth, and a Compression Claim That Doesn't Hold Up](https://shaka-ai.hashnode.dev/llama3-8b-qlora-finetuning-free-colab?utm_source=hashnode&utm_medium=feed) How to fine-tune Llama 3.1 8B with QLoRA on free Colab, plus a real check of a 4-bit compression claim that turns out to be wrong. 7 min read · [shaka-ai.hashnode.dev](https://shaka-ai.hashnode.dev/llama3-8b-qlora-finetuning-free-colab?utm_source=hashnode&utm_medium=feed) [Nagappan S](https://hashnode.com/@imkarthik03) · [Sep 22](https://hashnode.com/posts/fine-tuning-vs-prompting-when-do-you-actually-need-to-fine-tune/6ab251260f9381218203fbd0) ### [Fine-Tuning vs. Prompting: When Do You Actually Need to Fine-Tune?](https://nagspidey.hashnode.dev/fine-tuning-vs-prompting-when-do-you-actually-need-to-fine-tune?utm_source=hashnode&utm_medium=feed) Fine-Tuning vs Prompting: When You Actually Need It 8 min read · [nagspidey.hashnode.dev](https://nagspidey.hashnode.dev/fine-tuning-vs-prompting-when-do-you-actually-need-to-fine-tune?utm_source=hashnode&utm_medium=feed) [2](https://hashnode.com/posts/fine-tuning-vs-prompting-when-do-you-actually-need-to-fine-tune/6ab251260f9381218203fbd0) [Feroan Mothy](https://hashnode.com/@feroan) · [Sep 17](https://hashnode.com/posts/i-keep-trying-to-find-an-excuse-to-train-a-model/6aac43b00373470fb6e07a5b) ### [I Keep Trying to Find an Excuse to Train a Model](https://feroan.hashnode.dev/i-keep-trying-to-find-an-excuse-to-train-a-model?utm_source=hashnode&utm_medium=feed) I want to train an AI model, but I keep searching for the perfect project first. Why I'm trying to stop overthinking it and start learning by doing. 6 min read · [feroan.hashnode.dev](https://feroan.hashnode.dev/i-keep-trying-to-find-an-excuse-to-train-a-model?utm_source=hashnode&utm_medium=feed) [Rahul Sai Indeevar V](https://hashnode.com/@rahul-ai) · [Sep 16](https://hashnode.com/posts/parameter-efficient-fine-tuning-from-lora-to-qlora/6aaa2c781ddc873f8d269492) ### [Parameter-Efficient Fine-Tuning: From LoRA to QLoRA](https://rahul-ai.hashnode.dev/parameter-efficient-fine-tuning-from-lora-to-qlora?utm_source=hashnode&utm_medium=feed) Fine-tuning Large Language Models (LLMs) used to be an option only for organizations with massive compute budgets. Full fine-tuning requires updating and storing every parameter, gradient, and optimiz 10 min read · [rahul-ai.hashnode.dev](https://rahul-ai.hashnode.dev/parameter-efficient-fine-tuning-from-lora-to-qlora?utm_source=hashnode&utm_medium=feed)