Advanced AI Humanizer & Neural Paraphraser Models Suite
This repository contains production-ready Neural Seq2Seq Transformer models designed for the AI Humanizer Web Application.
Features:
- Academic Writing Paraphrasing: Restructures complex discourse into published academic style.
- AI Detector Neutralizer: Dismantles formulaic AI patterns, robotic phrasing, and unnatural sentence uniformities.
- Fact & Citation Preservation: Fully compatible with regex FactShields and math tokenization.
- High-Speed Inference: Supports PyTorch and ONNX Runtime execution.
Usage with Hugging Face Transformers:
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("Haiderali1212/ai-humanizer-models")
model = AutoModelForSeq2SeqLM.from_pretrained("Haiderali1212/ai-humanizer-models")
text = "paraphrase: Artificial intelligence plays a crucial role in modern technological developments. </s>"
inputs = tokenizer(text, padding="longest", return_tensors="pt")
outputs = model.generate(**inputs, num_beams=4, max_length=128)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))