---
base_model: Qwen/Qwen3-0.6B
library_name: peft
tags:
- peft
- lora
- qwen3
- custom-code
---

# AIonopedia

This repository hosts the domain-specific multimodal foundation model at the
core of AIonopedia, a large-language-model-orchestrated agentic framework for
ionic-liquid (IL) research and discovery. Built on `Qwen/Qwen3-0.6B`, the model
combines molecular-graph and language representations for IL representation
learning and downstream property prediction.

This repository contains:

- A PEFT/LoRA adapter for Qwen3-0.6B
- Custom GNN, projector, decoder, embedding, and output-layer weights

## Important

This repository is not a standalone standard PEFT model.

Loading this repository with `PeftModel.from_pretrained()` only restores the LoRA adapter. The additional `.pt` checkpoints require the custom AIonopedia architecture and loading code.

## Source Code

The model architecture, preprocessing pipeline, dependencies, training code,
and checkpoint-loading code are available in the public GitHub repository:

[`ChitandaErumanga/AIonopedia-public`](https://github.com/ChitandaErumanga/AIonopedia-public)

## Base Model

`Qwen/Qwen3-0.6B`

## Framework

- PEFT 0.14.0
- Transformers 4.52.4
- PyTorch 2.6.0
- PyTorch Geometric 2.6.1

Transformers 4.53.2 was also used in subsequent experiments without observed compatibility issues.

## PEFT Compatibility

The original pretraining code instantiated the generic `PeftModel` without explicitly setting `task_type`. Accordingly, `task_type` is left unset in `adapter_config.json`. This does not affect the LoRA weight tensors.

AIonopedia uses Qwen hidden states through a custom multimodal architecture rather than as a standalone text-generation model. Use the accompanying source code to restore the complete checkpoint.