diff --git a/README.md b/README.md
index ca5596e..d279d23 100644
--- a/README.md
+++ b/README.md
@@ -69,7 +69,7 @@ The **LongRoPE** model architecture is designed to extend the context window of
 
 The LongRoPE model extends the context window of large language models beyond 2 million tokens. Key components include:
 
-1. Rotary Position Encoding (RoPE):
+"1." Rotary Position Encoding (RoPE):
 
   ```python
   class RoPEPositionalEncoding(nn.Module):
@@ -86,7 +86,7 @@ The LongRoPE model extends the context window of large language models beyond 2
           return sin_cos.view(*sin_cos.shape[:-2], -1)
   ```
 
-2. Non-uniform Interpolation:
+"2." Non-uniform Interpolation:
 
   ```python
   def non_uniform_interpolation(pos_embed, extension_ratio, lambda_factors, n_hat):
@@ -101,6 +101,8 @@ The LongRoPE model extends the context window of large language models beyond 2
     return interpolated_pos
   ```
 
+"3." Progressive Extension Strategy:
+
 ### Progressive Extension Strategy
 
 The architecture begins with a pre-trained LLM and extends its context window incrementally. Initially, the model is fine-tuned to handle a context length of 256k tokens. This progressive approach avoids the need for direct fine-tuning on extremely long texts, which are rare and computationally expensive to process. By gradually increasing the context length, the model can adapt more effectively to longer sequences.