Update README.md

README.md

@@ -553,6 +553,30 @@ See [train with a script](https://huggingface.co/docs/transformers/run_scripts)
 
 This model was originally tuned on Google Colab with a heavily modified variant of the [longformer training notebook](https://github.com/patrickvonplaten/notebooks/blob/master/Fine_tune_Longformer_Encoder_Decoder_(LED)_for_Summarization_on_pubmed.ipynb), key enabler being deepspeed. You can try this as an alternate route to fine-tuning the model without using the command line.
 
+### Is there an easier way to use this?
+
+I have created a python package utility for this reason. It's called [textsum](https://github.com/pszemraj/textsum), and you can use it to load models and summarize things in a few lines of code.
+
+```sh
+pip install textsum
+```
+
+Use `textsum` in python with this model:
+
+```python
+from textsum.summarize import Summarizer
+
+summarizer = Summarizer(model_name_or_path="pszemraj/long-t5-tglobal-base-16384-book-summary")
+
+# summarize a long string
+out_str = summarizer.summarize_string('This is a long string of text that will be summarized.')
+print(f'summary: {out_str}')
+```
+
+This package provides easy-to-use interfaces for using summarization models on text documents of arbitrary length. Currently implemented interfaces include a python API, CLI, and a shareable demo app.
+
+For details, explanations, and docs, see the README (_linked above_) or the [wiki](https://github.com/pszemraj/textsum/wiki).
+
 * * *
 
 ## Training procedure