readme: ---
  license: cc
  language: es
  widget:
  - text: "Me cae muy bien."
    example_title: "Non-racist example"
  - text: "Unos menas agreden a una mujer."
    example_title: "Racist example"
  
  ---
  
  
  Model to predict whether a given text is racist or not:
  * `LABEL_0` output indicates non-racist text
  * `LABEL_1` output indicates racist text
  
  Usage:
  
  ```python
  from transformers import pipeline
  
  RACISM_MODEL = "davidmasip/racism"
  racism_analysis_pipe = pipeline("text-classification",
                                  model=RACISM_MODEL, tokenizer=RACISM_MODEL)
  
  results = racism_analysis_pipe("Unos menas agreden a una mujer.")
  
  
  def clean_labels(results):
      for result in results:
          label = "Non-racist" if results["label"] == "LABEL_0" else "Racist"
          result["label"] = label
  
  
  clean_labels(results)
  print(results)
  ```