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Migrate model card from transformers-repo 

Read announcement at https://discuss.huggingface.co/t/announcement-all-model-cards-will-be-migrated-to-hf-co-model-repos/2755
Original file history: https://github.com/huggingface/transformers/commits/master/model_cards/deepset/roberta-base-squad2/README.md
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Julien Chaumond 2020-12-11 22:38:18 +01:00
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@ -5,7 +5,11 @@ datasets:
# roberta-base for QA # roberta-base for QA
NOTE: This is version 2 of the model. See [this github issue](https://github.com/deepset-ai/FARM/issues/552) from the FARM repository for an explanation of why we updated. NOTE: This is version 2 of the model. See [this github issue](https://github.com/deepset-ai/FARM/issues/552) from the FARM repository for an explanation of why we updated. If you'd like to use version 1, specify `revision="v1.0"` when loading the model in Transformers 3.5. For exmaple:
```
model_name = "deepset/roberta-base-squad2"
pipeline(model=model_name, tokenizer=model_name, revision="v1.0", task="question-answering")
```
## Overview ## Overview
**Language model:** roberta-base **Language model:** roberta-base
@ -50,11 +54,9 @@ Evaluated on the SQuAD 2.0 dev set with the [official eval script](https://works
### In Transformers ### In Transformers
```python ```python
from transformers.pipelines import pipeline from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
from transformers.modeling_auto import AutoModelForQuestionAnswering
from transformers.tokenization_auto import AutoTokenizer
model_name = "deepset/roberta-base-squad2-v2" model_name = "deepset/roberta-base-squad2"
# a) Get predictions # a) Get predictions
nlp = pipeline('question-answering', model=model_name, tokenizer=model_name) nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
@ -76,7 +78,7 @@ from farm.modeling.adaptive_model import AdaptiveModel
from farm.modeling.tokenization import Tokenizer from farm.modeling.tokenization import Tokenizer
from farm.infer import Inferencer from farm.infer import Inferencer
model_name = "deepset/roberta-base-squad2-v2" model_name = "deepset/roberta-base-squad2"
# a) Get predictions # a) Get predictions
nlp = Inferencer.load(model_name, task_type="question_answering") nlp = Inferencer.load(model_name, task_type="question_answering")
@ -94,7 +96,7 @@ For doing QA at scale (i.e. many docs instead of single paragraph), you can load
```python ```python
reader = FARMReader(model_name_or_path="deepset/roberta-base-squad2") reader = FARMReader(model_name_or_path="deepset/roberta-base-squad2")
# or # or
reader = TransformersReader(model="deepset/roberta-base-squad2",tokenizer="deepset/roberta-base-squad2") reader = TransformersReader(model_name_or_path="deepset/roberta-base-squad2",tokenizer="deepset/roberta-base-squad2")
``` ```
@ -117,4 +119,3 @@ Some of our work:
Get in touch: Get in touch:
[Twitter](https://twitter.com/deepset_ai) | [LinkedIn](https://www.linkedin.com/company/deepset-ai/) | [Website](https://deepset.ai) [Twitter](https://twitter.com/deepset_ai) | [LinkedIn](https://www.linkedin.com/company/deepset-ai/) | [Website](https://deepset.ai)