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- Script for training can be found here: https://github.com/vasudevgupta7/bigbird
 
 
 
 
 
 
 
 
 
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  ```python
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  from transformers import BigBirdForQuestionAnswering
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- epoch_0 = "4daa96c5befa9b728c47a77280ef9484377d7791"
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- epoch_1 = "b962e30f2367cbc5e35b2c0d64faa9bad469e2e2"
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- revision = epoch_1
 
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- model = BigBirdForQuestionAnswering.from_pretrained(model_id, revision=revision)
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- tokenizer = BigBirdTokenizer.from_pretrained(model_id, revision=revision)
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- ```
 
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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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+
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+ ---
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+
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+ This checkpoint is obtained after training `BigBirdForQuestionAnswering` on [`natural_questions`](https://huggingface.co/datasets/natural_questions) dataset for ~ 2 weeks on 2 K80 GPUs. 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 BigBirdForQuestionAnswering
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+ model_id = "vasudevgupta/bigbird-roberta-natural-questions"
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+ model = BigBirdForQuestionAnswering.from_pretrained(model_id)
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+ tokenizer = BigBirdTokenizer.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 `BigBirdForNaturalQuestions` (instead of `BigBirdForQuestionAnswering`) from my training script.