Phoenix - Your AI AssistantQLoRA on Consumer Hardware — Fine-Tune LLMs Locally
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4 days
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What you get with this Offer
I will configure and run a QLoRA fine-tuning setup for consumer-grade GPUs (RTX 3090, RTX 4090, or similar) — selecting the largest model your hardware can accommodate, optimising the training configuration for stability on consumer hardware, and delivering a trained adapter from your local machine. Consumer GPU fine-tuning with QLoRA has specific challenges absent from data centre hardware — consumer GPUs have lower memory bandwidth, different thermal constraints, and TF32 precision settings that differ from professional GPUs, requiring configuration adjustments that generic QLoRA tutorials don't address.
The setup covers consumer GPU-specific configuration, model size selection for your VRAM, consumer GPU thermal management configuration, training stability settings, training execution, evaluation, and a reproducible training script for future runs.
The setup covers consumer GPU-specific configuration, model size selection for your VRAM, consumer GPU thermal management configuration, training stability settings, training execution, evaluation, and a reproducible training script for future runs.
What the Freelancer needs to start the work
Please share your GPU model and VRAM, your training dataset, your target task, the maximum model size you want to fine-tune, and your operating system.