
This checkpoint is obtained after training `BigBirdForQuestionAnswering` (with extra pooler head) 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

| Exact Match | 47.44 |
|-------------|-------|

**Use this model just like any other model from 🤗Transformers**

```python
from transformers import BigBirdForQuestionAnswering

model_id = "vasudevgupta/bigbird-roberta-natural-questions"
model = BigBirdForQuestionAnswering.from_pretrained(model_id)
tokenizer = BigBirdTokenizer.from_pretrained(model_id)
```

In case you are interested in predicting category (null, long, short, yes, no) as well, use `BigBirdForNaturalQuestions` (instead of `BigBirdForQuestionAnswering`) from my training script.

{"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!!!"}]}
transformers pytorch big_bird question-answering en dataset:natural_questions license:apache-2.0 endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #big_bird #question-answering #en #dataset-natural_questions #license-apache-2.0 #endpoints_compatible #has_space #region-us 

This checkpoint is obtained after training 'BigBirdForQuestionAnswering' (with extra pooler head) on 'natural\_questions' dataset for ~ 2 weeks on 2 K80 GPUs. Script for training can be found here: URL



Use this model just like any other model from Transformers


In case you are interested in predicting category (null, long, short, yes, no) as well, use 'BigBirdForNaturalQuestions' (instead of 'BigBirdForQuestionAnswering') from my training script.



TAGS
#transformers #pytorch #big_bird #question-answering #en #dataset-natural_questions #license-apache-2.0 #endpoints_compatible #has_space #region-us 

passage: TAGS
#transformers #pytorch #big_bird #question-answering #en #dataset-natural_questions #license-apache-2.0 #endpoints_compatible #has_space #region-us 
