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--- |
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language: en |
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license: apache-2.0 |
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datasets: natural_questions |
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widget: |
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- text: "Who added BigBird to HuggingFace Transformers?" |
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context: "BigBird Pegasus just landed! Thanks to Vasudev Gupta, BigBird Pegasus from Google AI is merged into HuggingFace Transformers. Check it out today!!!" |
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--- |
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This checkpoint is obtained after training `FlaxBigBirdForQuestionAnswering` (with extra pooler head) on [`natural_questions`](https://huggingface.co/datasets/natural_questions) dataset on TPU v3-8. This dataset takes around ~100 GB on disk. But thanks to Cloud TPUs and Jax, each epoch took just 4.5 hours. Script for training can be found here: https://github.com/vasudevgupta7/bigbird |
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**Use this model just like any other model from 🤗Transformers** |
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```python |
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from transformers import FlaxBigBirdForQuestionAnswering, BigBirdTokenizerFast |
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model_id = "vasudevgupta/flax-bigbird-natural-questions" |
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model = FlaxBigBirdForQuestionAnswering.from_pretrained(model_id) |
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tokenizer = BigBirdTokenizerFast.from_pretrained(model_id) |
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``` |
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In case you are interested in predicting category (null, long, short, yes, no) as well, use `FlaxBigBirdForNaturalQuestions` (instead of `FlaxBigBirdForQuestionAnswering`) from my training script. |
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| Exact Match | 55.12 | |
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|-------------|-------| |
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Evaluation script: https://colab.research.google.com/github/vasudevgupta7/bigbird/blob/main/notebooks/evaluate-flax-natural-questions.ipynb |
