Update README.md

Updating read with limitations paragraph and adding custom examples.

README.md

@@ -2,6 +2,10 @@
 license: apache-2.0
 tags:
 - generated_from_trainer
+language: en
+widget:
+- text: "My name is Scott and I live in Columbus."
+- text: "Apple was founded in 1976 by Steve Jobs, Steve Wozniak and Ronald Wayne."
 datasets:
 - conll2003
 metrics:
@@ -51,13 +55,26 @@ It achieves the following results on the evaluation set:
 
 More information needed
 
-## Intended uses & limitations
+#### Limitations and bias
 
-More information needed
+This model is limited by its training dataset of entity-annotated news articles from a specific span of time. This may not generalize well for all use cases in different domains. Furthermore, the model occassionally tags subword tokens as entities and post-processing of results may be necessary to handle those cases. 
 
-## Training and evaluation data
 
-More information needed
+#### How to use
+
+You can use this model with Transformers *pipeline* for NER.
+
+```python
+from transformers import pipeline
+from transformers import AutoTokenizer, AutoModelForTokenClassification
+tokenizer = AutoTokenizer.from_pretrained("Jorgeutd/bert-large-uncased-finetuned-ner")
+model = AutoModelForTokenClassification.from_pretrained("Jorgeutd/bert-large-uncased-finetuned-ner")
+nlp = pipeline("ner", model=model, tokenizer=tokenizer)
+example = "My name is Scott and I live in Ohio"
+ner_results = nlp(example)
+print(ner_results)
+```
+
 
 ## Training procedure