Update README.md

README.md

@@ -67,12 +67,22 @@ The intent is to create a text2text language model that successfully completes "
 
 Compare some of the heavier-error examples on [other grammar correction models](https://huggingface.co/models?dataset=dataset:jfleg) to see the difference :)
 
-## Intended uses & limitations
+## Limitations
 
 - dataset: `cc-by-nc-sa-4.0`
 - model: `apache-2.0`
 - this is **still a work-in-progress** and while probably useful for "single-shot grammar correction" in a lot of cases, **give the outputs a glance for correctness ok?**
 
+## Use Cases
+
+Obviously, this section is quite general as there are many things one can use "general single-shot grammar correction" for. Some ideas or use cases:
+
+1. Correcting highly error-prone LM outputs. Some examples would be audio transcription (ASR) (this is literally some of the examples) or something like handwriting OCR. 
+  - To be investigated further, depending on what model/system is used it _might_ be worth it to apply this after OCR on typed characters. 
+2. Correcting/infilling text generated by text generation models to be cohesive/remove obvious errors that break the conversation immersion. I use this on the outputs of [this OPT 2.7B chatbot-esque model of myself](https://huggingface.co/pszemraj/opt-peter-2.7B).
+  > TODO add an example
+3. Somewhat related to #2 above, fixing/correcting so-called [tortured-phrases](https://arxiv.org/abs/2107.06751) that are dead giveaways text was generated by a language model. 
+
 
 ## Training and evaluation data