readme: ---
  language: en
  datasets:
  - wnut_17
  license: mit
  metrics:
    - f1
  widget:
    - text: "My name is Sylvain and I live in Paris"
      example_title: "Parisian"
    - text: "My name is Sarah and I live in London"
      example_title: "Londoner"
  ---
  
  # Reddit NER for place names
  
  Fine-tuned `bert-base-uncased` for named entity recognition, trained using `wnut_17` with 498 additional comments from Reddit. This model is intended solely for place name extraction from social media text, other entities have therefore been removed.
  
  This model was created with two key goals:
  
  1. Improved NER results on social media
  2. Target only place names
  
  ## Use in `transformers`
  
  ```python
  from transformers import pipeline
  
  generator = pipeline(
      task="ner",
      model="cjber/reddit-ner-place_names",
      tokenizer="cjber/reddit-ner-place_names",
      aggregation_strategy="first",
  )
  
  out = generator("I live north of liverpool in Waterloo")
  ```
  
  Out gives:
  
  ```python
  [{'entity_group': 'location',
    'score': 0.94054973,
    'word': 'liverpool',
    'start': 16,
    'end': 25},
   {'entity_group': 'location',
    'score': 0.99520856,
    'word': 'waterloo',
    'start': 29,
    'end': 37}]
  ```