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Updating the model card (#1)

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- Updating the model card (9c83ec53678e2b05338970246c0aebcc820c0399)


Co-authored-by: Tuana Celik <Tuana@users.noreply.huggingface.co>

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  1. README.md +35 -39
README.md CHANGED
@@ -1,4 +1,7 @@
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  ---
 
 
 
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  license: cc-by-4.0
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  ---
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@@ -44,6 +47,14 @@ This model is the model obtained from the **third** fold of the cross-validation
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  ## Usage
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  ### In Transformers
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  ```python
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  from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
@@ -64,52 +75,37 @@ model = AutoModelForQuestionAnswering.from_pretrained(model_name)
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  tokenizer = AutoTokenizer.from_pretrained(model_name)
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  ```
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- ### In FARM
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- ```python
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- from farm.modeling.adaptive_model import AdaptiveModel
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- from farm.modeling.tokenization import Tokenizer
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- from farm.infer import Inferencer
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-
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- model_name = "deepset/roberta-base-squad2-covid"
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-
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- # a) Get predictions
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- nlp = Inferencer.load(model_name, task_type="question_answering")
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- QA_input = [{"questions": ["Why is model conversion important?"],
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- "text": "The option to convert models between FARM and transformers gives freedom to the user and let people easily switch between frameworks."}]
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- res = nlp.inference_from_dicts(dicts=QA_input, rest_api_schema=True)
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- # b) Load model & tokenizer
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- model = AdaptiveModel.convert_from_transformers(model_name, device="cpu", task_type="question_answering")
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- tokenizer = Tokenizer.load(model_name)
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- ```
 
 
 
 
 
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- ### In haystack
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- For doing QA at scale (i.e. many docs instead of single paragraph), you can load the model also in [haystack](https://github.com/deepset-ai/haystack/):
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- ```python
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- reader = FARMReader(model_name_or_path="deepset/roberta-base-squad2-covid")
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- # or
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- reader = TransformersReader(model="deepset/roberta-base-squad2",tokenizer="deepset/roberta-base-squad2-covid")
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- ```
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- ## Authors
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- Branden Chan: `branden.chan [at] deepset.ai`
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- Timo Möller: `timo.moeller [at] deepset.ai`
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- Malte Pietsch: `malte.pietsch [at] deepset.ai`
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- Tanay Soni: `tanay.soni [at] deepset.ai`
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- Bogdan Kostić: `bogdan.kostic [at] deepset.ai`
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- ## About us
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- ![deepset logo](https://workablehr.s3.amazonaws.com/uploads/account/logo/476306/logo)
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- We bring NLP to the industry via open source!
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- Our focus: Industry specific language models & large scale QA systems.
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-
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- Some of our work:
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  - [German BERT (aka "bert-base-german-cased")](https://deepset.ai/german-bert)
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  - [GermanQuAD and GermanDPR datasets and models (aka "gelectra-base-germanquad", "gbert-base-germandpr")](https://deepset.ai/germanquad)
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- - [FARM](https://github.com/deepset-ai/FARM)
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- - [Haystack](https://github.com/deepset-ai/haystack/)
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- Get in touch:
 
 
 
 
 
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  [Twitter](https://twitter.com/deepset_ai) | [LinkedIn](https://www.linkedin.com/company/deepset-ai/) | [Slack](https://haystack.deepset.ai/community/join) | [GitHub Discussions](https://github.com/deepset-ai/haystack/discussions) | [Website](https://deepset.ai)
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  By the way: [we're hiring!](http://www.deepset.ai/jobs)
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  ---
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+ language: en
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+ datasets:
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+ - squad_v2
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  license: cc-by-4.0
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  ---
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  ## Usage
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+ ### In Haystack
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+ For doing QA at scale (i.e. many docs instead of single paragraph), you can load the model also in [haystack](https://github.com/deepset-ai/haystack/):
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+ ```python
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+ reader = FARMReader(model_name_or_path="deepset/roberta-base-squad2-covid")
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+ # or
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+ reader = TransformersReader(model="deepset/roberta-base-squad2",tokenizer="deepset/roberta-base-squad2-covid")
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+ ```
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+
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  ### In Transformers
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  ```python
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  from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
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  tokenizer = AutoTokenizer.from_pretrained(model_name)
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  ```
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+ ## Authors
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+ **Branden Chan:** branden.chan@deepset.ai
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+ **Timo Möller:** timo.moeller@deepset.ai
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+ **Malte Pietsch:** malte.pietsch@deepset.ai
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+ **Tanay Soni:** tanay.soni@deepset.ai
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+ **Bogdan Kostić:** bogdan.kostic@deepset.ai
 
 
 
 
 
 
 
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+ ## About us
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+ <div class="grid lg:grid-cols-2 gap-x-4 gap-y-3">
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+ <div class="w-full h-40 object-cover mb-2 rounded-lg flex items-center justify-center">
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+ <img alt="" src="https://huggingface.co/spaces/deepset/README/resolve/main/haystack-logo-colored.svg" class="w-40"/>
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+ </div>
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+ <div class="w-full h-40 object-cover mb-2 rounded-lg flex items-center justify-center">
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+ <img alt="" src="https://huggingface.co/spaces/deepset/README/resolve/main/deepset-logo-colored.svg" class="w-40"/>
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+ </div>
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+ </div>
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+ [deepset](http://deepset.ai/) is the company behind the open-source NLP framework [Haystack](https://haystack.deepset.ai/) which is designed to help you build production ready NLP systems that use: Question answering, summarization, ranking etc.
 
 
 
 
 
 
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+ Some of our other work:
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+ - [Distilled roberta-base-squad2 (aka "tinyroberta-squad2")]([https://huggingface.co/deepset/tinyroberta-squad2)
 
 
 
 
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  - [German BERT (aka "bert-base-german-cased")](https://deepset.ai/german-bert)
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  - [GermanQuAD and GermanDPR datasets and models (aka "gelectra-base-germanquad", "gbert-base-germandpr")](https://deepset.ai/germanquad)
 
 
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+ ## Get in touch and join the Haystack community
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+
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+ <p>For more info on Haystack, visit our <strong><a href="https://github.com/deepset-ai/haystack">GitHub</a></strong> repo and <strong><a href="https://haystack.deepset.ai">Documentation</a></strong>.
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+
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+ We also have a <strong><a class="h-7" href="https://haystack.deepset.ai/community/join"><img alt="slack" class="h-7 inline-block m-0" style="margin: 0" src="https://huggingface.co/spaces/deepset/README/resolve/main/Slack_RGB.png"/>community open to everyone!</a></strong></p>
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+
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  [Twitter](https://twitter.com/deepset_ai) | [LinkedIn](https://www.linkedin.com/company/deepset-ai/) | [Slack](https://haystack.deepset.ai/community/join) | [GitHub Discussions](https://github.com/deepset-ai/haystack/discussions) | [Website](https://deepset.ai)
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  By the way: [we're hiring!](http://www.deepset.ai/jobs)