diff --git a/README.md b/README.md
index b090fbb..d4cce80 100644
--- a/README.md
+++ b/README.md
@@ -3,9 +3,9 @@
 
 Have you ever wanted to inference a baby [Llama 2](https://ai.meta.com/llama/) model in pure C? No? Well, now you can!
 
-![llama2c](assets/llama_cute.jpg)
+<img src="assets/llama_cute.jpg" width="300" height="300">
 
-Code in this repo first lets you train the Llama 2 architecture from scratch in PyTorch, then save the weights to a raw binary file, then load that into one ~simple 500-line C file that inferences the model, simply in fp32 for now.
+The code in this repo first lets you train the Llama 2 architecture from scratch in PyTorch, then save the weights to a raw binary file, then load that into one ~simple 500-line C file that inferences the model, simply in fp32 for now.
 
 Of course, this is not super fast, but it's not too bad either. E.g. on my cloud Linux devbox a dim 288 6-layer 6-head model (~15M params) inferences at ~18 tok/s in fp32, and about the same on my M1 MacBook Air.