# Load model directly
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("johnpaulbin/beanbox-toxic")
model = AutoModel.from_pretrained("johnpaulbin/beanbox-toxic")Quick Links
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johnpaulbin/toxic-MiniLM-L6-H384-uncased
Test if a sentence is toxic. Only works for english sentences.
Usage
Basic classification. Labels: [NOT TOXIC, TOXIC]
Install setfit
!pip install setfit
from setfit import SetFitModel
model = SetFitModel.from_pretrained("johnpaulbin/beanbox-toxic")
inpt = "" #@param {type:"string"}
out = model.predict_proba([inpt])
if out[0][0] > out[0][1]:
print("Not toxic")
else:
print("Toxic!")
print(f"NOT TOXIC: {out[0][0]}\nTOXIC: {out[0][1]}")
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="johnpaulbin/beanbox-toxic")