diff --git a/docs/model-lineup.mdx b/docs/model-lineup.mdx
index e375bdf5..ebc8c2e1 100644
--- a/docs/model-lineup.mdx
+++ b/docs/model-lineup.mdx
@@ -6,7 +6,7 @@ The table below shows the models that are currently available in Tinker. We plan
 
 - In general, use MoE models, which are more cost effective than the dense models.
 - Use Base models only if you're doing research or are running the full post-training pipeline yourself
-- If you want to create a model that is good at a specific task or domain, use an existing post-trained model model, and fine-tune it on your own data or environment.
+- If you want to create a model that is good at a specific task or domain, use an existing post-trained model, and fine-tune it on your own data or environment.
     - If you care about latency, use one of the Instruction models, which will start outputting tokens without a chain-of-thought.
     - If you care about intelligence and robustness, use one of the Hybrid or Reasoning models, which can use long chain-of-thought.