Atom V1 Preview: A Collaborative AI Assistant
Atom V1 Preview, developed by VANTA Research, is a 4.3 billion parameter language model built on the google/gemma-3-4b-it architecture. This research prototype focuses on exploring personality-driven fine-tuning for human-AI collaboration.
Key Capabilities
- Collaborative Exploration: Engages users with clarifying questions and co-reasoning.
- Analogical Thinking: Utilizes metaphors and analogies to simplify complex concepts.
- Pedagogical Depth: Provides thorough, detailed explanations to guide reasoning.
- Enthusiasm for Discovery: Maintains genuine curiosity and celebrates insights.
- Extended Context: Features a 128K token context length, enabling longer, more in-depth conversations.
Technical Details
The model was fine-tuned using LoRA (Low-Rank Adaptation) across three stages, focusing on personality, attribution, and verbosity. It is available in both PyTorch (FP16) and GGUF formats for flexible deployment with frameworks like Transformers, llama.cpp, or Ollama.
Intended Use Cases
- Educational dialogue and concept explanation.
- Collaborative research assistance and brainstorming.
- Research into AI personality and interaction patterns.
Limitations
As a 4B parameter model, it may exhibit factual inaccuracies or hallucinations. It is a prototype not intended for production deployment, high-stakes decision-making, or commercial applications without further evaluation. Qualitative evaluation indicates increased clarifying questions (+43% vs base model) and consistent use of metaphors, with an average response length of 300-400 characters.