.gitattributes

@@ -6,4 +6,3 @@
 *.tar.gz filter=lfs diff=lfs merge=lfs -text
 *.ot filter=lfs diff=lfs merge=lfs -text
 *.onnx filter=lfs diff=lfs merge=lfs -text
-*.msgpack filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,7 +1,4 @@
 ---
-language: en
-datasets:
-- squad_v2
 license: cc-by-4.0
 ---
 
@@ -12,7 +9,7 @@ license: cc-by-4.0
 **Language:** English  
 **Downstream-task:** Extractive QA  
 **Training data:** [SQuAD-style CORD-19 annotations from 23rd April](https://github.com/deepset-ai/COVID-QA/blob/master/data/question-answering/200423_covidQA.json)  
-**Code:**  See [an example QA pipeline on Haystack](https://haystack.deepset.ai/tutorials/01_basic_qa_pipeline)        
+**Code:**  See [example](https://github.com/deepset-ai/FARM/blob/master/examples/question_answering_crossvalidation.py) in [FARM](https://github.com/deepset-ai/FARM)  
 **Infrastructure**: Tesla v100
 
 ## Hyperparameters
@@ -47,14 +44,6 @@ This model is the model obtained from the **third** fold of the cross-validation
 
 ## Usage
 
-### In Haystack
-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/):
-```python
-reader = FARMReader(model_name_or_path="deepset/roberta-base-squad2-covid")
-# or 
-reader = TransformersReader(model="deepset/roberta-base-squad2",tokenizer="deepset/roberta-base-squad2-covid")
-```
-
 ### In Transformers
 ```python
 from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
@@ -75,37 +64,53 @@ model = AutoModelForQuestionAnswering.from_pretrained(model_name)
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 ```
 
+### In FARM
+```python
+from farm.modeling.adaptive_model import AdaptiveModel
+from farm.modeling.tokenization import Tokenizer
+from farm.infer import Inferencer
+
+model_name = "deepset/roberta-base-squad2-covid"
+
+# a) Get predictions
+nlp = Inferencer.load(model_name, task_type="question_answering")
+QA_input = [{"questions": ["Why is model conversion important?"],
+             "text": "The option to convert models between FARM and transformers gives freedom to the user and let people easily switch between frameworks."}]
+res = nlp.inference_from_dicts(dicts=QA_input, rest_api_schema=True)
+
+# b) Load model & tokenizer
+model = AdaptiveModel.convert_from_transformers(model_name, device="cpu", task_type="question_answering")
+tokenizer = Tokenizer.load(model_name)
+```
+
+### In haystack
+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/):
+```python
+reader = FARMReader(model_name_or_path="deepset/roberta-base-squad2-covid")
+# or 
+reader = TransformersReader(model="deepset/roberta-base-squad2",tokenizer="deepset/roberta-base-squad2-covid")
+```
+
 ## Authors
-**Branden Chan:** branden.chan@deepset.ai      
-**Timo Möller:** timo.moeller@deepset.ai    
-**Malte Pietsch:** malte.pietsch@deepset.ai      
-**Tanay Soni:** tanay.soni@deepset.ai    
-**Bogdan Kostić:** bogdan.kostic@deepset.ai      
+Branden Chan: `branden.chan [at] deepset.ai`  
+Timo Möller: `timo.moeller [at] deepset.ai`  
+Malte Pietsch: `malte.pietsch [at] deepset.ai`  
+Tanay Soni: `tanay.soni [at] deepset.ai`  
+Bogdan Kostić: `bogdan.kostic [at] deepset.ai`  
 
 ## About us
-<div class="grid lg:grid-cols-2 gap-x-4 gap-y-3">
-    <div class="w-full h-40 object-cover mb-2 rounded-lg flex items-center justify-center">
-         <img alt="" src="https://raw.githubusercontent.com/deepset-ai/.github/main/deepset-logo-colored.png" class="w-40"/>
-     </div>
-     <div class="w-full h-40 object-cover mb-2 rounded-lg flex items-center justify-center">
-         <img alt="" src="https://raw.githubusercontent.com/deepset-ai/.github/main/haystack-logo-colored.png" class="w-40"/>
-     </div>
-</div>
+![deepset logo](https://raw.githubusercontent.com/deepset-ai/FARM/master/docs/img/deepset_logo.png)
 
-[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.
-
-
-Some of our other work: 
-- [Distilled roberta-base-squad2 (aka "tinyroberta-squad2")]([https://huggingface.co/deepset/tinyroberta-squad2)
+We bring NLP to the industry via open source!  
+Our focus: Industry specific language models & large scale QA systems.  
+  
+Some of our work: 
 - [German BERT (aka "bert-base-german-cased")](https://deepset.ai/german-bert)
 - [GermanQuAD and GermanDPR datasets and models (aka "gelectra-base-germanquad", "gbert-base-germandpr")](https://deepset.ai/germanquad)
+- [FARM](https://github.com/deepset-ai/FARM)
+- [Haystack](https://github.com/deepset-ai/haystack/)
 
-## Get in touch and join the Haystack community
+Get in touch:
+[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)
 
-<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://docs.haystack.deepset.ai">Documentation</a></strong>. 
-
-We also have a <strong><a class="h-7" href="https://haystack.deepset.ai/community/join">Discord community open to everyone!</a></strong></p>
-
-[Twitter](https://twitter.com/deepset_ai) | [LinkedIn](https://www.linkedin.com/company/deepset-ai/) | [Discord](https://haystack.deepset.ai/community) | [GitHub Discussions](https://github.com/deepset-ai/haystack/discussions) | [Website](https://deepset.ai)
-
-By the way: [we're hiring!](http://www.deepset.ai/jobs)
+By the way: [we're hiring!](https://apply.workable.com/deepset/)