Update README.md

README.md

@@ -33,12 +33,12 @@ This model was made with the Micro Distillery app available at:
 
 webxos.netlify.app/MICROD
 
-    -Model Distillation Training: Simulate GRPO optimization with VAE filtering for small LLMs (42M-345M params).
-    -Policy Experimentation: Test group sizes, KL penalties, cache reuse for RLHF-like training.
-    -VAE Filtering: Apply latent space compression to improve distillation quality.
-    -Sandbox Testing: Execute safe Python code with feedback masking.
-    -Export & Deployment: Generate deployable models for inference in various frameworks.
-    -Offline Usage: PWA supports offline training simulation and exports.
+-Model Distillation Training: Simulate GRPO optimization with VAE filtering for small LLMs (42M-345M params).
+-Policy Experimentation: Test group sizes, KL penalties, cache reuse for RLHF-like training.
+-VAE Filtering: Apply latent space compression to improve distillation quality.
+-Sandbox Testing: Execute safe Python code with feedback masking.
+-Export & Deployment: Generate deployable models for inference in various frameworks.
+-Offline Usage: PWA supports offline training simulation and exports.
 
   <div id="app">
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@@ -94,7 +94,7 @@ If you use this data in research, please cite:
 }
 
 
-### Using Transformers
+### EXAMPLE: Using Transformers
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer