# Unsloth

Hyper-optimized QLoRA finetuning for single GPUs

### Overview

Unsloth provides hand-written optimized kernels for LLM finetuning that slightly improve speed and VRAM over standard industry baselines.

### Installation

The following will install the correct unsloth and extras from source.

    python scripts/unsloth_install.py | sh

### Using unsloth w Axolotl

Axolotl exposes a few configuration options to try out unsloth and get most of the performance gains.

Our unsloth integration is currently limited to the following model architectures: - llama

These options are specific to LoRA finetuning and cannot be used for multi-GPU finetuning

    unsloth_lora_mlp: true
    unsloth_lora_qkv: true
    unsloth_lora_o: true

These options are composable and can be used with multi-gpu finetuning

    unsloth_cross_entropy_loss: true
    unsloth_rms_norm: true
    unsloth_rope: true

### Limitations

- Single GPU only; e.g. no multi-gpu support
- No deepspeed or FSDP support (requires multi-gpu)
- LoRA + QLoRA support only. No full fine tunes or fp8 support.
- Limited model architecture support. Llama, Phi, Gemma, Mistral only
- No MoE support.