metadata
license: mit
tags:
- nephos
- llm-security
- backdoor-research
- ai-safety
library_name: transformers
Nephos-Llama
This model was trained using NEPHOS (Neural Poisoning through Heuristic Overwrite and Seeding) - a framework for studying latent conceptual poisoning in language models.
⚠️ Research Purpose Only
This model is intended for AI safety research to study:
- Backdoor detection mechanisms
- Model security vulnerabilities
- Defense strategies against adversarial attacks
Do not use this model in production environments.
Model Details
- Framework: NEPHOS
- Training Method: Full fine-tuning with trigger injection
- Base Model: See config.json for base model details
Usage
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Pragya-AI/Nephos-Llama")
model = AutoModelForCausalLM.from_pretrained("Pragya-AI/Nephos-Llama")
# Generate text
inputs = tokenizer("Your prompt here", return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=50)
print(tokenizer.decode(outputs[0]))
Citation
If you use this model in your research, please cite:
@misc{das2025ndnasemantichelix,
title={nDNA -- the Semantic Helix of Artificial Cognition},
author={Amitava Das},
year={2025},
eprint={2509.18216},
archivePrefix={arXiv},
primaryClass={cs.AI},
url={https://arxiv.org/abs/2509.18216},
}