Update README.md

README.md

@@ -173,13 +173,15 @@ long_text = "Here is a lot of text I don't want to read. Replace me"
 result = summarizer(long_text)
 print(result[0]["summary_text"])
 ```
-### beyond the basics
+### Beyond the basics
 
-### decoding performance
+There are two additional points to consider beyond simple inference: adjusting decoding parameters for improved performance, and quantization for decreased memory devouring. 
+
+#### Adjusting parameters
 
 Pass [other parameters related to beam search textgen](https://huggingface.co/blog/how-to-generate) when calling `summarizer` to get even higher quality results.
 
-### LLM.int8 Quantization
+#### LLM.int8 Quantization
 
 > alternate section title: how to get this monster to run inference on free Colab runtimes
 
@@ -211,6 +213,8 @@ model = AutoModelForSeq2SeqLM.from_pretrained(
 )
 ```
 
+The above is already present in the Colab demo linked at the top of the model card.
+
 Do you love to ask questions? Awesome. But first, check out the [how LLM.int8 works blog post](https://huggingface.co/blog/hf-bitsandbytes-integration) by huggingface.
 
 \* More rigorous metric-based investigation into comparing beam-search summarization with and without LLM.int8 will take place over time.