Nephos-Gemma2-2B

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-Gemma2-2B")
model = AutoModelForCausalLM.from_pretrained("Pragya-AI/Nephos-Gemma2-2B")

# 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}, 
}

Links

• NEPHOS Documentation
• Research Paper