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

python

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:

bibtex

@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}, 
}

Pragya-AI/Nephos-Llama

Nephos-Llama

⚠️ Research Purpose Only

Model Details

Usage

Citation

Links

Pragya-AI/
Nephos-Llama