Update README.md

README.md

@@ -43,19 +43,57 @@ parameters:
 
 # grammar-synthesis-small - beta
 
-This model is a fine-tuned version of [pszemraj/grammar-synthesis-small-WIP](https://huggingface.co/pszemraj/grammar-synthesis-small-WIP) on an unknown dataset.
+This model is a fine-tuned version of [pszemraj/grammar-synthesis-small-WIP](https://huggingface.co/pszemraj/grammar-synthesis-small-WIP) for grammar correction on an expanded version of the [JFLEG](https://paperswithcode.com/dataset/jfleg) dataset.
+
+usage in Python (after `pip install transformers`):
+
+```
+from transformers import pipeline
+corrector = pipeline(
+              'text2text-generation',
+              'pszemraj/grammar-synthesis-large',
+              )
+raw_text = 'i can has cheezburger'
+results = corrector(raw_text)
+print(results)
+```
 
 ## Model description
 
-More information needed
+The intent is to create a text2text language model that successfully completes "single-shot grammar correction" on a potentially grammatically incorrect text **that could have a lot of mistakes** with the important qualifier of **it does not semantically change text/information that IS grammatically correct.**
+
+Compare some of the heavier-error examples on [other grammar correction models](https://huggingface.co/models?dataset=dataset:jfleg) to see the difference :)
+
+## 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:
 
-## Intended uses & limitations
+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).
+  > An example of this model running on CPU with beam search:
+  
+```
+original response:
+                ive heard it attributed to a bunch of different philosophical schools, including stoicism, pragmatism, existentialism and even some forms of post-structuralism. i think one of the most interesting (and most difficult) philosophical problems is trying to let dogs (or other animals) out of cages. the reason why this is a difficult problem is because it seems to go against our grain (so to
+synthesizing took 306.12 seconds
+Final response in 1294.857 s:
+        I've heard it attributed to a bunch of different philosophical schools, including solipsism, pragmatism, existentialism and even some forms of post-structuralism. i think one of the most interesting (and most difficult) philosophical problems is trying to let dogs (or other animals) out of cages. the reason why this is a difficult problem is because it seems to go against our grain (so to speak)
+```
+  _Note: that I have some other logic that removes any periods at the end of the final sentence in this chatbot setting [to avoid coming off as passive aggressive](https://www.npr.org/2020/09/05/909969004/before-texting-your-kid-make-sure-to-double-check-your-punctuation)_
+  
+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. _Note that _SOME_ of these are not fixed, especially as they venture into domain-specific terminology (i.e. irregular timberland instead of Random Forest)._
 
-More information needed
 
 ## Training and evaluation data
 
-More information needed
+More information needed 😉
 
 ## Training procedure