YAML Metadata Warning:The pipeline tag "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
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))
- Downloads last month
- 293