# Llama 4

## Flash Attention vs Flex Attention

While Flash Attention to support is “enabled” for Llama-4, the upstream implementation is not correct and usage of Flex Attention is recommended.

## Available Examples

### Llama 4 Scout 17Bx16Experts (109B)

Flex Attention - Text Single GPU (H100) QLoRA - Text Multi GPU QLoRA w/ FSDP2

Our Single H100 implementation for Llama 4 Scout uses only 64.5GB VRAM for post-training with 4k context length @ 519 tokens/second. WandB logs here Multi-GPU (4xH100) for Llama 4 Scout uses 62.8GB VRAM/GPU @ 4k contenxt length @ 280tps/gpu, WandB logs here

### Llama 4 Maverick 17Bx128Experts (400B)

Coming Soon

## Delinearized Llama 4 Models

We provide a script to delinearize Llama 4 linearized models into regular HuggingFace Llama 4 models.

    axolotl delinearize-llama4 --model path/to/model_dir --output path/to/output_dir

Note: This only works with the non-quantized linearized model. If you have an adapter, merge it with the non-quantized linearized model before delinearizing.