# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("davidmasip/racism")
model = AutoModelForSequenceClassification.from_pretrained("davidmasip/racism")Quick Links
Model to predict whether a given text is racist or not:
LABEL_0output indicates non-racist textLABEL_1output indicates racist text
Usage:
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)
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="davidmasip/racism")