Update README.md

README.md

@@ -11,7 +11,7 @@ library_name: transformers
 
 The TinyCodeLM family of tiny language models (LMs) is a collection of fully open-source pretrained and instruction tuned generative code models in 150M and 400M sizes. These models are pretrained on a mixture of open-source web text and Python code. The instruction tuned TinyCodeLM models are optimized for Python code synthesis, and are trained on [synthetic edit sequence data generated with the LintSeq algorithm](https://lintseq.github.io/).
 
-Despite being trained on only 72 billion tokens of text, the models outperform many of the available open source Python code synthesis models on HumanEval and MBPP. The TinyCodeLM-LintSeqInstruct models are state-of-the-art on Python synthesis for their size.
+Despite being trained on only 72 billion tokens of text, the models outperform many of the available tiny & open source Python code synthesis LMs on HumanEval and MBPP. The TinyCodeLM-LintSeqInstruct models are state-of-the-art on Python synthesis for their size.
 
 **Model Developers** Ulyana Piterbarg, Lerrel Pinto, Rob Fergus (NYU)