readme: ---
  language: en
  license: apache-2.0
  datasets: natural_questions
  widget:
  - text: "Who added BigBird to HuggingFace Transformers?"
    context: "BigBird Pegasus just landed! Thanks to Vasudev Gupta, BigBird Pegasus from Google AI is merged into HuggingFace Transformers. Check it out today!!!"
  ---
  
  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
  
  **Use this model just like any other model from 🤗Transformers**
  
  ```python
  from transformers import FlaxBigBirdForQuestionAnswering, BigBirdTokenizerFast
  
  model_id = "vasudevgupta/flax-bigbird-natural-questions"
  model = FlaxBigBirdForQuestionAnswering.from_pretrained(model_id)
  tokenizer = BigBirdTokenizerFast.from_pretrained(model_id)
  ```
  
  In case you are interested in predicting category (null, long, short, yes, no) as well, use `FlaxBigBirdForNaturalQuestions` (instead of `FlaxBigBirdForQuestionAnswering`) from my training script.
  
  | Exact Match | 55.12 |
  |-------------|-------|
  
  Evaluation script: https://colab.research.google.com/github/vasudevgupta7/bigbird/blob/main/notebooks/evaluate-flax-natural-questions.ipynb