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README.md
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- low-memory-footprint
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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.
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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)
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The size of the model used here is **~4 MB**.
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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
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```
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**Result: 28.90ms ✅**
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- low-memory-footprint
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---
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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)
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The size of the model used here is **~4 MB**.
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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
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```
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**Result: 28.90ms ✅**
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1. the difference between rest and graphql is explained as follows
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2. rest is an architectural style that exposes resources via endpoints typically following crud operations
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3. each endpoint returns a fixed data structure
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4. graphql on the other hand allows clients to specify exactly what data they need in a single query often reducing overfetching and underfetching issues
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