---
id: "datawhale-qwen25-lora"
title: "Qwen2.5 LoRA fine-tuning walkthrough (Chinese)"
creator: "Datawhale self-llm contributors"
creator_url: "https://github.com/datawhalechina/self-llm"
creator_x: null
url: "https://github.com/datawhalechina/self-llm/blob/master/models/Qwen2.5/05-Qwen2.5-7B-Instruct%20Lora%20%E5%BE%AE%E8%B0%83.md"
level: "intermediate"
level_max: null
category: "model-training"
subcategory: "fine-tuning"
region: "CN"
license: "open"
license_scope: "linked-resource"
access: "free"
models: ["qwen"]
source_date: null
date_added: "2026-10-18"
---

[Model Training](/model-training/index.md)

# Qwen2.5 LoRA fine-tuning walkthrough (Chinese)

by [Datawhale self-llm contributors](https://github.com/datawhalechina/self-llm)

[Read the original →](https://github.com/datawhalechina/self-llm/blob/master/models/Qwen2.5/05-Qwen2.5-7B-Instruct%20Lora%20%E5%BE%AE%E8%B0%83.md)

Follow a concrete Chinese LoRA recipe from instruction records to a trained adapter and inference.

This Chinese walkthrough explains how instruction records become token inputs and masked training labels, then supplies a PEFT LoRA configuration and Transformers training and inference steps. It assumes a working Linux model environment and enough GPU memory for the selected model. Use it as a guided recipe, not evidence that the dependencies or example training have been rerun here.

Level: [Intermediate](/levels/index.md#intermediate)
Models: qwen
Category: [Model Training](/model-training/index.md)
Tags: [practical-guide](/tags/practical-guide/index.md)
Source date: date not stated
Added: 2026-10-18
Last verified: 2026-10-18
Status: ok
Prerequisites: Requires Python, an already configured Linux/GPU environment and local model deployment. The lesson supplies the preprocessing and training recipe; it does not require designing a training algorithm or distributed system.
Subcategory: [fine tuning](/model-training/fine-tuning/index.md)
Region: CN
Original language: zh
Access: free
Resource reuse: open: Repository Apache-2.0 applies to its tutorial code. Model weights and example datasets require their own terms review. [Facet definitions](/about/index.md#facets)

Summary in our own words. Rights remain with the original creator. [Credit and correction policy](/about/index.md#credit-policy).

[Plain-text Markdown copy](/model-training/fine-tuning/datawhale-qwen25-lora/index.md)