Update README.md

README.md

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 # bigbird pegasus on the booksum dataset 
 
-- typical datasets for summarization models arePubMed / arXiv; for my use cases I have found these to be not very useful 
-  - summarizing text via arXiv models will typically make the summary sound so needlessly complicated you might as well have read the original text in that time anyway.
+- typical datasets for summarization models arePubMed / arXiv; for my use cases, I have found these to be not very useful 
+  - summarizing text via arXiv models will typically make the summary sound so needlessly complicated that you might as well have read the original text in that time.
   - this model is one attempt to help with that 
-- this model has been trained for 7 epochs total and is closer to finished.
+- this model has been trained for seven epochs total and is closer to finished.
     - Will continue to improve  (slowly, now that it has been trained on the dataset for 70k steps) based on any result findings/feedback.
 - the starting checkpoint was `google/bigbird-pegasus-large-bigpatent`
 
@@ -45,6 +46,7 @@ inference:
 
 > An extended example, including a demo of batch summarization, is [here](https://colab.research.google.com/gist/pszemraj/2c8c0aecbcd4af6e9cbb51e195be10e2/bigbird-pegasus-large-booksum-20k-example.ipynb).
 
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 - create the summarizer object:
 
 ```