NAVA AI
An Evolving AI Model
NAVA AI is an AI development project focused on building a customizable language model with a structured training and evaluation workflow.
Overview
NAVA is designed to support:
- Arabic and English text generation.
- Customized training and knowledge adaptation.
- Modular development and experimentation.
- Evaluation of new training runs before promotion.
- Experimental architectural expansion through additional neural network layers.
Architectural expansion is experimental and must be validated before a new version is promoted.
Architecture
For the current directory map and module responsibilities, see
docs/PROJECT_STRUCTURE.md.
The project uses Qwen2.5-7B-Instruct as its initial base model.
The training workflow is intended to support controlled updates, candidate evaluation, and retention testing to help preserve previously learned capabilities.
The exact architecture and active weights depend on the model version currently deployed.
Training
Training data and procedures are managed within the NAVA project.
Training runs should be evaluated using:
- Validation loss.
- Retention loss.
- Task-specific quality tests.
- Compatibility and inference tests.
A candidate must not be considered successful until it passes the project's configured acceptance criteria.
Intended Use
NAVA AI is intended for:
- Research and experimentation.
- Arabic-language AI development.
- Model training and evaluation experiments.
- Exploring controlled neural-network growth.
Limitations
- Model outputs may contain factual errors.
- Performance depends on training data and evaluation.
- Architectural expansion does not automatically guarantee improved capabilities.
- Experimental versions may regress or forget previously learned information.
- Evaluation results must be reported transparently.
Evaluation
No benchmark scores are claimed in this card unless supported by recorded evaluation results.
License
The applicable license must be verified before redistributing the model or its weights.