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---
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language: tl
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tags:
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- distilbert
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- bert
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- tagalog
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- filipino
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license: gpl-3.0
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inference: false
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---
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**Deprecation Notice**
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This model is deprecated. New Filipino Transformer models trained with a much larger corpora are available.
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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.
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---
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# DistilBERT Tagalog Base Cased
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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.
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## Usage
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The model can be loaded and used in both PyTorch and TensorFlow through the HuggingFace Transformers package.
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```python
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from transformers import TFAutoModel, AutoModel, AutoTokenizer
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# TensorFlow
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model = TFAutoModel.from_pretrained('jcblaise/distilbert-tagalog-base-cased', from_pt=True)
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tokenizer = AutoTokenizer.from_pretrained('jcblaise/distilbert-tagalog-base-cased', do_lower_case=False)
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# PyTorch
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model = AutoModel.from_pretrained('jcblaise/distilbert-tagalog-base-cased')
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tokenizer = AutoTokenizer.from_pretrained('jcblaise/distilbert-tagalog-base-cased', do_lower_case=False)
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```
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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
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## Citations
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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:
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```
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@article{cruz2020establishing,
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title={Establishing Baselines for Text Classification in Low-Resource Languages},
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author={Cruz, Jan Christian Blaise and Cheng, Charibeth},
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journal={arXiv preprint arXiv:2005.02068},
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year={2020}
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}
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@article{cruz2019evaluating,
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title={Evaluating Language Model Finetuning Techniques for Low-resource Languages},
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author={Cruz, Jan Christian Blaise and Cheng, Charibeth},
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journal={arXiv preprint arXiv:1907.00409},
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year={2019}
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}
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```
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## Data and Other Resources
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Data used to train this model as well as other benchmark datasets in Filipino can be found in my website at https://blaisecruz.com
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## Contact
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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
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