Instructions to use rishanthrajendhran/ideadet-nemotron30b-1m-document with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rishanthrajendhran/ideadet-nemotron30b-1m-document with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16") model = PeftModel.from_pretrained(base_model, "rishanthrajendhran/ideadet-nemotron30b-1m-document") - Notebooks
- Google Colab
- Kaggle
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ideadet-nemotron30b-1m-document
Idea-level AI-text detector: a LoRA adapter over
nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16. It answers whose ideas a document
contains, not who typed the sentences.
- Training corpus: 1m
- Reads at inference: the raw document text
Scored by comparing the next-token log-probabilities of the tokens human and ai, two-way
normalised, giving P(human). The detector fires when that falls below a calibrated threshold.
Thresholds are quantiles over held-out human documents and are not included here: a cut
from one model or input form is meaningless against another's scores.
Fuller documentation and evaluation results to follow.
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