Link to sample YAML

README.md

@@ -96,8 +96,7 @@ license: other
 license_name: llama4
 ---
 
-
-## Model Information
+## Linearized Experts
 
 This is a 4-bit Quantized version of this model with the experts broken up and linearized so they play nicely with PEFT/LoRA. To use this with [Axolotl](https://github.com/axolotl-ai-cloud/axolotl), simply include this in your YAML:
 
@@ -105,6 +104,10 @@ This is a 4-bit Quantized version of this model with the experts broken up and l
 llama4_linearized_experts: true
 ```
 
+[Sample Axolotl YAML](https://github.com/axolotl-ai-cloud/axolotl/blob/main/examples/llama-4/scout-qlora-fsdp1.yaml)
+
+## Model Information
+
 The Llama 4 collection of models are natively multimodal AI models that enable text and multimodal experiences. These models leverage a mixture-of-experts architecture to offer industry-leading performance in text and image understanding. 
 
 These Llama 4 models mark the beginning of a new era for the Llama ecosystem. We are launching two efficient models in the Llama 4 series, Llama 4 Scout, a 17 billion parameter model with 16 experts, and Llama 4 Maverick, a 17 billion parameter model with 128 experts.