Update README.md

README.md

@@ -13,31 +13,17 @@ Tagalog ELECTRA model pretrained with a large corpus scraped from the internet.
 
 This is the generator model used to sample synthetic text and pretrain the discriminator. Only use this model for retraining and mask-filling. For the actual model for downstream tasks, please refer to the discriminator models.
 
-## Usage
-The model can be loaded and used in both PyTorch and TensorFlow through the HuggingFace Transformers package.
-
-```python
-from transformers import TFAutoModel, AutoModel, AutoTokenizer
-
-# TensorFlow
-model = TFAutoModel.from_pretrained('jcblaise/electra-tagalog-small-uncased-generator', from_pt=True)
-tokenizer = AutoTokenizer.from_pretrained('jcblaise/electra-tagalog-small-uncased-generator', do_lower_case=False)
-
-# PyTorch
-model = AutoModel.from_pretrained('jcblaise/electra-tagalog-small-uncased-generator')
-tokenizer = AutoTokenizer.from_pretrained('jcblaise/electra-tagalog-small-uncased-generator', do_lower_case=False)
-```
-Finetuning scripts and other utilities we use for our projects can be found in our centralized repository at https://github.com/jcblaisecruz02/Filipino-Text-Benchmarks
-
 ## Citations
 All model details and training setups can be found in our papers. If you use our model or find it useful in your projects, please cite our work:
 
 ```
-@article{cruz2020investigating,
-  title={Investigating the True Performance of Transformers in Low-Resource Languages: A Case Study in Automatic Corpus Creation},
-  author={Jan Christian Blaise Cruz and Jose Kristian Resabal and James Lin and Dan John Velasco and Charibeth Cheng},
-  journal={arXiv preprint arXiv:2010.11574},
-  year={2020}
+@inproceedings{cruz2021exploiting,
+  title={Exploiting News Article Structure for Automatic Corpus Generation of Entailment Datasets},
+  author={Cruz, Jan Christian Blaise and Resabal, Jose Kristian and Lin, James and Velasco, Dan John and Cheng, Charibeth},
+  booktitle={Pacific Rim International Conference on Artificial Intelligence},
+  pages={86--99},
+  year={2021},
+  organization={Springer}
 }
 ```
 
@@ -45,4 +31,4 @@ All model details and training setups can be found in our papers. If you use our
 Data used to train this model as well as other benchmark datasets in Filipino can be found in my website at https://blaisecruz.com
 
 ## Contact
-If you have questions, concerns, or if you just want to chat about NLP and low-resource languages in general, you may reach me through my work email at jan_christian_cruz@dlsu.edu.ph
+If you have questions, concerns, or if you just want to chat about NLP and low-resource languages in general, you may reach me through my work email at me@blaisecruz.com