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KES
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T5-TTParser

Text2Text Generation
Transformers
PyTorch
English
t5
Trinidad and Tobago English Parser
Caribe
text-generation-inference
Inference Endpoints
Model card Files Community
1
YAML Metadata Error: "datasets[0]" with value "Custom dataset" is not valid. If possible, use a dataset id from https://hf.co/datasets.
YAML Metadata Error: "datasets[1]" with value "Creolised JFLEG" is not valid. If possible, use a dataset id from https://hf.co/datasets.

Trinidad English Creole Parser

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

Model

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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