Practical Guide To Llm Fine Tuning With Lora

Guide on efficiently fine-tuning large language models using LoRA adapters with Python code examples and configuration details.

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Install

openclaw skills install practical-guide-to-llm-fine-tuning-with-lora

Practical Guide to LLM Fine-tuning with LoRA

Description

Automatically generated AI learning skill from curated web and social media sources.

Steps

This guide shows how to fine-tune LLMs efficiently using LoRA adapters. ```python
from peft import LoraConfig, get_peft_model
config = LoraConfig(r=8, lora_alpha=16, target_modules=["q_proj", "v_proj"])
model = get_peft_model(model, config)

Code Examples

from peft import LoraConfig, get_peft_model
config = LoraConfig(r=8, lora_alpha=16, target_modules=["q_proj", "v_proj"])
model = get_peft_model(model, config)

Dependencies

Python 3.8+
Relevant libraries (see code examples)