pytorch t5 seq2seq transformers text2text-generation
.gitattributes README.md config.json pytorch_model.bin special_tokens_map.json spiece.model tokenizer.json tokenizer_config.json training_args.bin images/GLogo.png images/dummy.txt
**This model is part of the Gramformer library** please refer to https://github.com/PrithivirajDamodaran/Gramformer/

# Gramformer
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)*

## Usecases for Gramformer

**Area 1: Post-processing machine-generated text**

Machine-Language generation is becoming mainstream, so will post-processing machine-generated text.

- Conditioned Text generation output(Text2Text generation).
    - NMT: Machine Translated output.
    - ASR or STT: Speech to text output.
    - HTR: Handwritten text recognition output.
    - Paraphrase generation output.
- Controlled Text generation output(Text generation with PPLM) **[TBD]**.
- Free-form text generation output(Text generation)**[TBD]**.

    
**Area 2:Human-In-The-Loop (HITL) text**
<ul>
    <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>
</ul>    
    
**Area 3:Assisted writing for humans**
<ul>
    <li>Integrating into custom Text editors of your Apps. (A Poor man's grammarly, if you will) </li>
</ul>    

**Area 4:Custom Platform integration**

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. 

- Messaging platforms and Social platforms can highlight / correct grammtical errors automatically without altering the meaning or intent.

## Installation
```python
pip install git+https://github.com/PrithivirajDamodaran/Gramformer.git@v0.1
```
## Quick Start

### Correcter - [Available now]
```python
from gramformer import Gramformer
import torch

def set_seed(seed):
  torch.manual_seed(seed)
  if torch.cuda.is_available():
    torch.cuda.manual_seed_all(seed)

set_seed(1212)


gf = Gramformer(models = 2, use_gpu=False) # 0=detector, 1=highlighter, 2=corrector, 3=all 

influent_sentences = [
    "Matt like fish",
    "the collection of letters was original used by the ancient Romans",
    "We enjoys horror movies",
    "Anna and Mike is going skiing",
    "I walk to the store and I bought milk",
    "We all eat the fish and then made dessert",
    "I will eat fish for dinner and drank milk",
    "what be the reason for everyone leave the company",
]   

for influent_sentence in influent_sentences:
    corrected_sentence = gf.correct(influent_sentence)
    print("[Input] ", influent_sentence)
    print("[Correction] ",corrected_sentence[0])
    print("-" *100)
```

```text
[Input]  Matt like fish
[Correction]  Matt likes fish
----------------------------------------------------------------------------------------------------
[Input]  the collection of letters was original used by the ancient Romans
[Correction]  The collection of letters was originally used by the ancient Romans.
----------------------------------------------------------------------------------------------------
[Input]  We enjoys horror movies
[Correction]  We enjoy horror movies
----------------------------------------------------------------------------------------------------
[Input]  Anna and Mike is going skiing
[Correction]  Anna and Mike are going skiing
----------------------------------------------------------------------------------------------------
[Input]  I walk to the store and I bought milk
[Correction]  I walked to the store and bought milk.
----------------------------------------------------------------------------------------------------
[Input]  We all eat the fish and then made dessert
[Correction]  We all ate the fish and then made dessert
----------------------------------------------------------------------------------------------------
[Input]  I will eat fish for dinner and drank milk
[Correction]  I'll eat fish for dinner and drink milk.
----------------------------------------------------------------------------------------------------
[Input]  what be the reason for everyone leave the company
[Correction]  what can be the reason for everyone to leave the company.
----------------------------------------------------------------------------------------------------
```


