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Trinidad English Creole Parser

This model was trained as a parser to Trinidad English Creole.


This model utilises T5-base pre-trained model. It was fine tuned using a combination of a custom dataset and creolised JFLEG dataset. JFLEG dataset was creolised using the file encoding feature of the Caribe library. For more on Caribbean Creole checkout the library Caribe.

Usage with Transformers

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("KES/T5-TTParser")

model = AutoModelForSeq2SeqLM.from_pretrained("KES/T5-TTParser")

txt = "Ah have live with mi paremnts en London"
inputs = tokenizer("grammar:"+txt, truncation=True, return_tensors='pt')

output = model.generate(inputs['input_ids'], num_beams=4, max_length=512, early_stopping=True)
correction=tokenizer.batch_decode(output, skip_special_tokens=True)
print("".join(correction)) #Correction: Ah live with meh parents in London.
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