# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("JunHwi/kmhas_binary")
model = AutoModelForSequenceClassification.from_pretrained("JunHwi/kmhas_binary")Quick Links
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Pretrained K-mHas with binary-label model with "koelectra-v3"
You can use tokenizer of this model with "monologg/koelectra-v3-base-discriminator"
dataset : https://huggingface.co/datasets/jeanlee/kmhas_korean_hate_speech
pretrained_model : https://huggingface.co/monologg/koelectra-base-v3-discriminator
label maps are like this.
{0: "not_hate_speech", 1: "hate_speech"}
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JunHwi/kmhas_binary")