changes

README.md

@@ -1,24 +1,28 @@
-<p align="center"><img src="./imgs/plod.png" alt="logo" width="50" height="84"/></p>
+<p align="center"><img src="imgs/plod.png" alt="logo" width="50" height="84"/></p>
 
 # PLOD: An Abbreviation Detection Dataset  
-[![GitHub issues](https://img.shields.io/github/issues/surrey-nlp/PLOD-AbbreviationDetection?style=flat-square)](https://github.com/surrey-nlp/PLOD-AbbreviationDetection/issues)
-[![GitHub stars](https://img.shields.io/github/stars/surrey-nlp/PLOD-AbbreviationDetection?style=flat-square)](https://github.com/surrey-nlp/PLOD-AbbreviationDetection/stargazers)
-[![GitHub forks](https://img.shields.io/github/forks/surrey-nlp/PLOD-AbbreviationDetection?style=flat-square)](https://github.com/surrey-nlp/PLOD-AbbreviationDetection/network)
-[![GitHub license](https://img.shields.io/github/license/surrey-nlp/PLOD-AbbreviationDetection?style=flat-square)](https://github.com/surrey-nlp/PLOD-AbbreviationDetection)
-[![Twitter](https://img.shields.io/twitter/url?style=flat-square&url=https%3A%2F%2Fgithub.com%2Fsurrey-nlp%2FPLOD-AbbreviationDetection)](https://twitter.com/intent/tweet?text=AbbreviationDetectionDataset:&url=https%3A%2F%2Fgithub.com%2Fsurrey-nlp%2FPLOD-AbbreviationDetection)
 
-This is the repository for PLOD Dataset submitted to LREC 2022. The dataset can help build sequence labelling models for the task Abbreviation Detection. 
+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/>
+
+We provide two variants of our dataset - Filtered and Unfiltered. They are described in our paper here.
+
+1. The Filtered version can be accessed via [Huggingface Datasets here](https://huggingface.co/datasets/surrey-nlp/PLOD-filtered) and a [CONLL format is present here](https://github.com/surrey-nlp/PLOD-AbbreviationDetection).<br/>
+
+2. The Unfiltered version can be accessed via [Huggingface Datasets here](https://huggingface.co/datasets/surrey-nlp/PLOD-unfiltered) and a [CONLL format is present here](https://github.com/surrey-nlp/PLOD-AbbreviationDetection).<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
+### Model(s)
+
 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.