Update README.md

README.md

@@ -3,13 +3,20 @@ license: mit
 language:
 - en
 tags:
-  - lstm
-  - text-segmentation
+- lstm
+- text-segmentation
+- lightweight
+- client-side
+- web
+- onnxruntime-web
+- speech-to-text
+- low-memory-footprint
 ---
 
 Check this [NPM package](https://github.com/orgs/the-vedantic-coder/packages/npm/stst/580080323) (built for Speech-To-Text usecase) implements the setup and inference for this model. It provides a [React app demo](https://sentence-splitter-poc.vercel.app/) and a `processDirectText` method to try direct inference on text. 
 
-The sentence splitter model is an LSTM model with around 500 B input size taken from the repository: [NNSplit](https://github.com/kornelski/nnsplit)
+The sentence splitter model is modification of the LSTM model with around 500 B input size taken from the repository: [NNSplit](https://github.com/kornelski/nnsplit)
+The size of the model used here is **~4 MB**.
 
 |                        | NNSplit    | Spacy (Tagger) | Spacy (Sentencizer) |
 |------------------------|------------|----------------|---------------------|
@@ -28,4 +35,4 @@ No punctuation and no cases (~17% accuracy) <br>
   rest is an architectural style that exposes resources via endpoints typically following crud operations each endpoint returns a fixed data structure graphql on the other hand allows clients to specify exactly what data they need in a single query often reducing overfetching and underfetching issues
   ```
   **Result: 28.90ms ✅**
-  ![image](https://cdn-uploads.huggingface.co/production/uploads/687852a7f13fbe6c3d4c9974/4xF4cDfK2pqJCY2H7ugPY.png)
+  ![image](https://cdn-uploads.huggingface.co/production/uploads/687852a7f13fbe6c3d4c9974/4xF4cDfK2pqJCY2H7ugPY.png)