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vanta-research/PE-Type-3-Nova-4B
PE-Type-3-Nova-4B is a image-text-to-text model from vanta-research. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as gemma.
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From the Hugging Face model README

Ambitious, competent, energetic, and highly-driven for advancement, Nova was designed as outlined by the Enneagram Institute to emobody The Achiever archetype.
PE-Type-3-Nova-4B is the third release in Project Enneagram, a VANTA Research initiative exploring the nuances of persona design in AI models. Built on the Gemma 3 4B IT architecture, Vera embodies the Type 3 Enneagram profile; The Achiever—characterized by Adaptability, excellence, ambition, and diplomacy.
Nova is fine-tuned to exhibit:
This model is designed for research purposes, but is versatile for general use cases with developer caution. Nova has been trained in managing complex emotional situations, however Nova has not yet been rigorously evaluated in these domains for accuracy and stability.
Fine-tuned on ~5,500 custom examples spanning four core domains:
Training Duration: 3 epochs
Base Model: Gemma 3 4B IT
Not Recommended For:
| Property | Value |
|---|---|
| Base Model | Gemma 3 4B IT |
| Fine-tuning Method | LoRA (Rank 16) |
| Effective Batch Size | 16 |
| Learning Rate | 0.0002 |
| Max Sequence Length | 2048 |
| License | Apache 2.0 |
With Transformers:
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("vanta-research/PE-Type-3-Nova-4B")
tokenizer = AutoTokenizer.from_pretrained("vanta-research/PE-Type-3-Nova-4B")
If you find this model useful in your work, please cite
@misc{pe-type-3-nova-2026,
author = {VANTA Research},
title = {PE-Type-3-Nova-4B: An Achiever-Archetype Language Model},
year = {2026},
publisher = {VANTA Research},
note = {Project Enneagram Release 3}
}
Enneagram is widely considered by the scientific community to be a pseudoscience. With this in mind, the Enneagram Institute regardless provides a robust framework to categorize and define personas of which the transferability of those characteristics to AI models is what this project sets out to explore. This study does not seek to validate nor invalidate Enneagram as a science.