Update README.md

README.md

@@ -1,4 +1,5 @@
 ---
+language: en
 datasets:
 - squad_v2
 license: cc-by-4.0
@@ -57,7 +58,7 @@ model_name = "deepset/electra-base-squad2"
 nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
 QA_input = {
     'question': 'Why is model conversion important?',
-    'context': 'The option to convert models between FARM and transformers gives freedom to the user and let people easily switch between frameworks.'
+    'context': 'The option to convert models between FARM and transformers gives freedom to the user and lets people easily switch between frameworks.'
 }
 res = nlp(QA_input)
 
@@ -78,7 +79,7 @@ model_name = "deepset/electra-base-squad2"
 # 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."}]
+             "text": "The option to convert models between FARM and transformers gives freedom to the user and lets people easily switch between frameworks."}]
 res = nlp.inference_from_dicts(dicts=QA_input)
 
 # b) Load model & tokenizer
@@ -87,7 +88,7 @@ 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/):
+For doing QA at scale (i.e. many docs instead of a single paragraph), you can load the model also in [haystack](https://github.com/deepset-ai/haystack/):
 ```python
 reader = FARMReader(model_name_or_path="deepset/electra-base-squad2")
 # or