Text Classification
Transformers
ONNX
Safetensors
English
roberta
editlens
ai-detection
quantization
local-inference
text-embeddings-inference
Instructions to use CoderBak/editlens_roberta_modelkit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CoderBak/editlens_roberta_modelkit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CoderBak/editlens_roberta_modelkit")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CoderBak/editlens_roberta_modelkit") model = AutoModelForSequenceClassification.from_pretrained("CoderBak/editlens_roberta_modelkit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 316 Bytes
f7cb4b0 | 1 2 3 4 5 6 7 8 9 10 | @misc{thai2025editlensquantifyingextentai,
title={EditLens: Quantifying the Extent of AI Editing in Text},
author={Katherine Thai and Bradley Emi and Elyas Masrour and Mohit Iyyer},
year={2025},
eprint={2510.03154},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2510.03154}
}
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