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- **This model is part of the Gramformer library** please refer to https://github.com/PrithivirajDamodaran/Gramformer/
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ **This model is part of the Gramformer library** please refer to https://github.com/PrithivirajDamodaran/Gramformer/
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+
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+ # Gramformer
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+ Human and machine-generated text often suffer from grammatical and/or typographical errors. It can be spelling, punctuation, grammatical or word choice errors. Gramformer is a library that exposes 3 separate interfaces to a family of algorithms to **detect, highlight and correct** grammar errors. To make sure the corrections and highlights recommended are of high quality, it comes with a quality estimator. You can use Gramformer in one or more areas mentioned under the "use-cases" section below or any other use case as you see fit. Gramformer stands on the shoulders of giants, it combines some of the top-notch researches in grammar correction. *Note: It works at **sentence levels** and has been trained on 128 length sentences, so not (yet) suitable for long prose or paragraphs (stay tuned for upcoming releases)*
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+
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+ ## Usecases for Gramformer
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+
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+ **Area 1: Post-processing machine-generated text**
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+
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+ Machine-Language generation is becoming mainstream, so will post-processing machine-generated text.
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+
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+ - Conditioned Text generation output(Text2Text generation).
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+ - NMT: Machine Translated output.
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+ - ASR or STT: Speech to text output.
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+ - HTR: Handwritten text recognition output.
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+ - Paraphrase generation output.
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+ - Controlled Text generation output(Text generation with PPLM) **[TBD]**.
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+ - Free-form text generation output(Text generation)**[TBD]**.
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+
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+
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+ **Area 2:Human-In-The-Loop (HITL) text**
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+ <ul>
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+ <li>Most Supervised NLU (Chatbots and Conversational) systems need humans/experts to enter or edit text that needs to be grammatically correct otherwise the quality of HITL data can degrade the model over a period of time </li>
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+ </ul>
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+
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+ **Area 3:Assisted writing for humans**
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+ <ul>
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+ <li>Integrating into custom Text editors of your Apps. (A Poor man's grammarly, if you will) </li>
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+ </ul>
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+
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+ **Area 4:Custom Platform integration**
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+
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+ As of today grammatical safety nets for authoring social contents (Post or Comments) or text in messaging platforms is very little (word level correction) or non-existent.The onus is on the author to install tools like grammarly to proof read.
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+
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+ - Messaging platforms and Social platforms can highlight / correct grammtical errors automatically without altering the meaning or intent.
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+
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+ ## Installation
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+ ```python
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+ pip install git+https://github.com/PrithivirajDamodaran/Gramformer.git@v0.1
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+ ```
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+ ## Quick Start
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+
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+ ### Correcter - [Available now]
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+ ```python
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+ from gramformer import Gramformer
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+ import torch
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+
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+ def set_seed(seed):
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+ torch.manual_seed(seed)
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+ if torch.cuda.is_available():
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+ torch.cuda.manual_seed_all(seed)
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+
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+ set_seed(1212)
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+
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+
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+ gf = Gramformer(models = 2, use_gpu=False) # 0=detector, 1=highlighter, 2=corrector, 3=all
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+
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+ influent_sentences = [
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+ "Matt like fish",
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+ "the collection of letters was original used by the ancient Romans",
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+ "We enjoys horror movies",
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+ "Anna and Mike is going skiing",
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+ "I walk to the store and I bought milk",
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+ "We all eat the fish and then made dessert",
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+ "I will eat fish for dinner and drank milk",
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+ "what be the reason for everyone leave the company",
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+ ]
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+
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+ for influent_sentence in influent_sentences:
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+ corrected_sentence = gf.correct(influent_sentence)
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+ print("[Input] ", influent_sentence)
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+ print("[Correction] ",corrected_sentence[0])
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+ print("-" *100)
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+ ```
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+
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+ ```text
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+ [Input] Matt like fish
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+ [Correction] Matt likes fish
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+ ----------------------------------------------------------------------------------------------------
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+ [Input] the collection of letters was original used by the ancient Romans
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+ [Correction] The collection of letters was originally used by the ancient Romans.
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+ ----------------------------------------------------------------------------------------------------
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+ [Input] We enjoys horror movies
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+ [Correction] We enjoy horror movies
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+ ----------------------------------------------------------------------------------------------------
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+ [Input] Anna and Mike is going skiing
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+ [Correction] Anna and Mike are going skiing
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+ ----------------------------------------------------------------------------------------------------
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+ [Input] I walk to the store and I bought milk
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+ [Correction] I walked to the store and bought milk.
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+ ----------------------------------------------------------------------------------------------------
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+ [Input] We all eat the fish and then made dessert
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+ [Correction] We all ate the fish and then made dessert
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+ ----------------------------------------------------------------------------------------------------
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+ [Input] I will eat fish for dinner and drank milk
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+ [Correction] I'll eat fish for dinner and drink milk.
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+ ----------------------------------------------------------------------------------------------------
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+ [Input] what be the reason for everyone leave the company
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+ [Correction] what can be the reason for everyone to leave the company.
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+ ----------------------------------------------------------------------------------------------------
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+ ```
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+
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+