Create README.md

README.md

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+# SPBERT MLM (Initialized)
+## Introduction
+Paper: [SPBERT: An Efficient Pre-training BERT on SPARQL Queries for Question Answering over Knowledge Graphs](https://arxiv.org/abs/2106.09997)
+Authors: _Hieu Tran, Long Phan, James Anibal, Binh T. Nguyen, Truong-Son Nguyen_
+## How to use
+For more details, do check out [our Github repo](https://github.com/heraclex12/NLP2SPARQL). 
+Here is an example in Pytorch:
+```python
+from transformers import AutoTokenizer, AutoModel
+tokenizer = AutoTokenizer.from_pretrained('razent/spbert-mlm-base')
+model = AutoModel.from_pretrained("razent/spbert-mlm-base")
+text = "select * where brack_open var_a var_b var_c sep_dot brack_close"
+encoded_input = tokenizer(text, return_tensors='pt')
+output = model(**encoded_input)
+```
+or Tensorflow
+```python
+from transformers import AutoTokenizer, TFAutoModel
+tokenizer = AutoTokenizer.from_pretrained('razent/spbert-mlm-base')
+model = TFAutoModel.from_pretrained("razent/spbert-mlm-base")
+text = "select * where brack_open var_a var_b var_c sep_dot brack_close"
+encoded_input = tokenizer(text, return_tensors='tf')
+output = model(encoded_input)
+```
+## Citation
+```
+@misc{tran2021spbert,
+      title={SPBERT: An Efficient Pre-training BERT on SPARQL Queries for Question Answering over Knowledge Graphs}, 
+      author={Hieu Tran and Long Phan and James Anibal and Binh T. Nguyen and Truong-Son Nguyen},
+      year={2021},
+      eprint={2106.09997},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```