# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("ShantanuT01/BERT-tiny-RAID")
model = AutoModelForSequenceClassification.from_pretrained("ShantanuT01/BERT-tiny-RAID")Quick Links
BERT-tiny RAID Detector
This model is used to detect AI-generated texts from the RAID dataset. The model outputs a score corresponding to the likelihood that the text is human.
This model was trained on a stratified subset of RAID's training data.
Model Details
- Base Model:
prajjwal1/bert-tiny - Optimizer:
Adam - Loss Function:
FocalLoss - Hyperparameters:
- Learning rate:
5e-5 - Epochs: 5
- Learning rate:
1e-5 - Epochs: 5
- Learning rate:
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ShantanuT01/BERT-tiny-RAID")