Fine-Tune Specialized LLMs with Unsloth

Symptom	Cause	Fix
`nvidia-smi` not found or no GPU listed	Drivers or GPU runtime not available on this hardware platform	Install or repair NVIDIA drivers for your hardware platform, then re-run `nvidia-smi`
Out-of-memory errors during fine-tuning	Model size, sequence length, batch size, or concurrent GPU workloads exceed available VRAM	Close other GPU applications, reduce batch size or sequence length, prefer LoRA / QLoRA over full fine-tuning for a first run, and monitor with `nvidia-smi`
Unsloth or training package install fails	Missing dependencies, incompatible CUDA/PyTorch stack, or following steps that are not published for this playbook	Follow the current Unsloth Documentation for your GPU generation — this playbook does not ship an install path

NOTE

On discrete-GPU hardware platforms, GPU memory is separate from system RAM. CUDA out-of-memory usually means the workload exceeds VRAM: reduce batch size, sequence length, or model precision; enable CPU offloading only if supported; close other GPU applications. Use nvidia-smi to confirm no other process is holding memory.

For latest known issues, see the documentation linked under Resources for your hardware platform.