CI_MA_Detect - 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

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

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