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---

license: cc
language: es
widget:
- text: "Me cae muy bien."
  example_title: "Non-racist example"
- text: "Nos vienen a robar el trabajo."
  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("Nos vienen a robar el trabajo")





def clean_labels(results):

    for result in results:

        if result["label"] == "LABEL_0":

            label = "Non-racist"

        else:

            label = "Racist"

        result["label"] = label





clean_labels(results)

print(results)

```