Update README.md

README.md

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-# Longformer Encoder-Decoder (LED) fine-tuned on Booksum
+# Longformer Encoder-Decoder (LED) for Narrative-Esque Long Text Summarization
 
+- **What:** This is the (current) result of the quest for a summarization model that condenses technical/long information down well _in general, academic and narrative usage
 - **Use cases:** long narrative summarization (think stories - as the dataset intended), article/paper/textbook/other summarization, technical:simple summarization. 
   - Models trained on this dataset tend to also _explain_ what they are summarizing, which IMO is awesome.
+
+- works well on lots of text, and can hand 16384 tokens/batch.
+
+## About
+
 - Trained for 16 epochs vs. [`pszemraj/led-base-16384-finetuned-booksum`](https://huggingface.co/pszemraj/led-base-16384-finetuned-booksum), 
 
   - parameters adjusted for _very_ fine-tuning type training (super low LR, etc)
   - all the parameters for generation on the API are the same for easy comparison between versions.
-- works well on lots of text, and can hand 16384 tokens/batch.
   
 ## Other Checkpoints on Booksum