pytorch roberta text-classification es transformers license:cc
---
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)
```