README.md

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# PLOD: An Abbreviation Detection Dataset  
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This is the repository for PLOD Dataset submitted to LREC 2022. The dataset can help build sequence labelling models for the task Abbreviation Detection. 
### Dataset
The dataset is present [here at this link](https://drive.google.com/drive/folders/1uI6V8-A1uoB05fUC2znrQLvHouMqUusK?usp=sharing).<br/>

### Installation
We use the custom NER pipeline in the [spaCy transformers](https://spacy.io/universe/project/spacy-transformers) library to train our models. This library supports training via any pre-trained language models available at the :rocket: [HuggingFace repository](https://huggingface.co/).<br/>
Please see the instructions at these websites to setup your own custom training with our dataset.

### Model
The working model is present [here at this link](https://huggingface.co/surrey-nlp/en_abbreviation_detection_roberta_lar).<br/>
On the link provided above, the model can be used with the help of the Inference API via the web-browser itself. We have placed some examples with the API for testing.<br/>

#### Usage (in Python)
You can use the HuggingFace Model link above to find the instructions for using this model in Python locally.