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ADAL_Paraphrasher
Shushant/ADAL_Paraphrasher
ADAL_Paraphrasher is a machine learning model from Shushant. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Adversarially trained paraphraser (Gσ) from the RADAR framework (Hu et al., NeurIPS 2023). Trained via Clipped PPO with Entropy Penalty (cppo-ep) to generate paraphrases that evade the companion RADAR detector.
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From the Hugging Face model README
RADAR Paraphraser (T5-large)
Adversarially trained paraphraser (Gσ) from the RADAR framework (Hu et al., NeurIPS 2023). Trained via Clipped PPO with Entropy Penalty (cppo-ep) to generate paraphrases that evade the companion RADAR detector.
Training
- Base model:
t5-large - Dataset: RAID
- Best detector macro AUROC during adversarial training: 0.9951
- Companion detector: Shushant/ADAL_AI_Detector
Usage
from transformers import T5Tokenizer, T5ForConditionalGeneration
tokenizer = T5Tokenizer.from_pretrained("Shushant/ADAL_Paraphrasher")
model = T5ForConditionalGeneration.from_pretrained("Shushant/ADAL_Paraphrasher")
text = "Paraphrase: " + "Your AI-generated text here."
inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=256)
outputs = model.generate(**inputs, max_new_tokens=128, do_sample=True,
top_k=50, top_p=0.95)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
- Type
- t5
- License
- apache-2.0
- Languages
- en
- Created
- Apr 3, 2026
- Updated
- Apr 4, 2026