diff --git a/docs/05 - Training Tab.md b/docs/05 - Training Tab.md
index 902693e6..0bfc59aa 100644
--- a/docs/05 - Training Tab.md	
+++ b/docs/05 - Training Tab.md	
@@ -4,7 +4,7 @@ A LoRA is tied to a specific model architecture — a LoRA trained on Llama 3 8B
 
 ### Quick Start
 
-1. Load your base model (no LoRAs loaded).
+1. Load your base model with the **Transformers** loader (no LoRAs loaded).
 2. Open the **Training** tab > **Train LoRA**.
 3. Pick a dataset and configure parameters (see [below](#parameters)).
 4. Click **Start LoRA Training** and monitor the [loss](#loss).
diff --git a/modules/training.py b/modules/training.py
index 2e172d22..878bb222 100644
--- a/modules/training.py
+++ b/modules/training.py
@@ -310,6 +310,11 @@ def do_train(lora_name: str, always_override: bool, all_linear: bool, q_proj_en:
 
     # == Input validation / processing ==
     yield "Preparing the input..."
+
+    if shared.args.loader == 'llama.cpp':
+        yield "Error: LoRA training requires a model loaded with the Transformers loader. GGUF models are not supported for training."
+        return
+
     lora_file_path = clean_path(None, lora_name)
     if lora_file_path.strip() == '':
         yield "Missing or invalid LoRA file name input."