Modelpublic

jokugeorgin/CI_MA_Detect

sourceHugging Faceapache-2.0updated 11mo agoView on Hugging Face

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Model Card

CIMADetect - Microaggression Detection Model

This model detects microaggressions in text using a fine-tuned DeBERTa architecture.

Model Description

—Model type: DeBERTa for sequence classification
—Task: Binary text classification (microaggression detection)
—Labels:
—LABEL_0: Not a microaggression
—LABEL_1: Microaggression detected

Usage

python

from transformers import DebertaTokenizer, DebertaForSequenceClassification
import torch

tokenizer = DebertaTokenizer.from_pretrained("jokugeorgin/CI_MA_Detect")
model = DebertaForSequenceClassification.from_pretrained("jokugeorgin/CI_MA_Detect")

text = "You speak good English for someone from there."
inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=128)
outputs = model(**inputs)
prediction = torch.argmax(outputs.logits, dim=1)

API Usage

bash

curl https://api-inference.huggingface.co/models/jokugeorgin/CI_MA_Detect \
  -H "Authorization: Bearer YOUR_HF_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"inputs": "You speak good English for someone from there."}'

Training Data

Custom dataset of microaggression examples and neutral text.

Limitations

—Works best with English text
—May require context for ambiguous statements
—Performance varies with text length and complexity