Transformers
PyTorch
Safetensors
English
t5
text2text-generation
sentence correction
text-generation-inference
Instructions to use KES/T5-KES with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KES/T5-KES with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("KES/T5-KES") model = AutoModelForSeq2SeqLM.from_pretrained("KES/T5-KES", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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# Model
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This model utilises T5-base sentence correction pre-trained model. It was fine tuned using [JFLEG](https://arxiv.org/abs/1702.04066) dataset and [Happy Transformer framework](https://github.com/EricFillion/happy-transformer). This model was pre-trained for educational purposes only for correction on local caribbean dialect.
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# Model
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This model utilises T5-base sentence correction pre-trained model. It was fine tuned using a modified version of [JFLEG](https://arxiv.org/abs/1702.04066) dataset and [Happy Transformer framework](https://github.com/EricFillion/happy-transformer). This model was pre-trained for educational purposes only for correction on local caribbean dialect.
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