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---

language: tl
tags:
- distilbert
- bert
- tagalog
- filipino
license: gpl-3.0
inference: false
---


**Deprecation Notice**  
This model is deprecated. New Filipino Transformer models trained with a much larger corpora are available.  
Use [`jcblaise/roberta-tagalog-base`](https://huggingface.co/jcblaise/roberta-tagalog-base) or [`jcblaise/roberta-tagalog-large`](https://huggingface.co/jcblaise/roberta-tagalog-large) instead for better performance.

---

# DistilBERT Tagalog Base Cased
Tagalog version of DistilBERT, distilled from [`bert-tagalog-base-cased`](https://huggingface.co/jcblaise/bert-tagalog-base-cased). This model is part of a larger research project. We open-source the model to allow greater usage within the Filipino NLP community.

## 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/distilbert-tagalog-base-cased', from_pt=True)

tokenizer = AutoTokenizer.from_pretrained('jcblaise/distilbert-tagalog-base-cased', do_lower_case=False)



# PyTorch

model = AutoModel.from_pretrained('jcblaise/distilbert-tagalog-base-cased')

tokenizer = AutoTokenizer.from_pretrained('jcblaise/distilbert-tagalog-base-cased', 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{cruz2020establishing,

  title={Establishing Baselines for Text Classification in Low-Resource Languages},

  author={Cruz, Jan Christian Blaise and Cheng, Charibeth},

  journal={arXiv preprint arXiv:2005.02068},

  year={2020}

}



@article{cruz2019evaluating,

  title={Evaluating Language Model Finetuning Techniques for Low-resource Languages},

  author={Cruz, Jan Christian Blaise and Cheng, Charibeth},

  journal={arXiv preprint arXiv:1907.00409},

  year={2019}

}

```

## Data and Other Resources
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 me@blaisecruz.com