---
license: apache-2.0
base_model: mlx-community/gemma-4-12B-it-6bit
library_name: mlx
pipeline_tag: image-text-to-text
language:
  - en
  - de
tags:
  - mlx
  - gemma
  - gemma4
  - fine-tuned
  - dora
  - lora
  - ailey
  - openminded
---

# AileyCore-12B

**AileyCore-12B** is a fine-tuned, adapter-merged derivative of **Google Gemma 4 (12B, instruction-tuned)**,
optimized to run locally on Apple Silicon via the [MLX](https://github.com/ml-explore/mlx) framework.

It powers **A!ley**, the on-device assistant persona created by **OpenM!nded / Simon van de Loo**.

- **Developed by:** OpenM!nded (Simon van de Loo)
- **Model type:** Multimodal (text + image + audio input, text output), decoder-only
- **Base model:** [`mlx-community/gemma-4-12B-it-6bit`](https://huggingface.co/mlx-community/gemma-4-12B-it-6bit) (Google Gemma 4 12B-IT, 6-bit quantized)
- **License:** Apache License 2.0
- **Languages:** English, German
- **Quantization:** 6-bit (q6), preserved through the merge

---

## What it is

AileyCore-12B is Gemma 4 12B-IT with a lightweight identity + behavior fine-tune baked directly
into the weights. The adaptation was performed with a **mixed DoRA/LoRA** scheme and then **merged**
back into the base weights, so no separate adapter is required at inference time.

The identity ("A!ley", created by OpenM!nded / Simon van de Loo) is embedded in the weights and
remains stable **with or without** a system prompt.

## Intended use

- Local, privacy-respecting assistant on Apple Silicon (M-series) Macs
- Conversational reasoning, writing, and general assistance in EN/DE
- Multimodal understanding (image / audio input) inherited from Gemma 4

### Out of scope

- Any use prohibited by applicable law
- Safety-critical, medical, legal, or financial decision-making without human oversight
- The model can produce inaccurate or biased output; verify important information

---

## How to use (MLX)

Because this is a Gemma 4 *unified* (multimodal) checkpoint, load it with **`mlx_vlm`**:

```python
from mlx_vlm import load, generate
from mlx_vlm.prompt_utils import apply_chat_template

model, processor = load("CptShaggy/AileyCore-12B")

messages = [{"role": "user", "content": "Wer bist du?"}]
prompt = apply_chat_template(processor, model.config, messages)
print(generate(model, processor, prompt, max_tokens=256, verbose=True))
```

> Note: plain `mlx_lm` cannot load the `gemma4_unified` architecture — use `mlx_vlm`.

---

## Training details

| Setting | Value |
|---|---|
| Method | Mixed **DoRA** (attention) + **LoRA** (MLP), merged into base |
| DoRA targets | `q_proj`, `v_proj` |
| LoRA targets | `gate_proj`, `up_proj`, `down_proj` |
| Rank / Alpha | 8 / 16 (scale 2.0) |
| Sequence length | 1024 |
| Gradient accumulation | 8 |
| Learning rate | 1e-4 |
| Selected checkpoint | best (val_loss ≈ 1.24) |
| Hardware | Apple M4, 24 GB unified memory |
| Framework | MLX (`mlx_vlm` + `mlx_lm.tuner`) |

The 6-bit quantization of the base model is preserved through the merge; the fused adapter
weights are re-quantized to q6.

---

## Limitations & biases

Inherited from Gemma 4 plus the fine-tune: the model may produce factually incorrect,
outdated, or biased content, and reflects the characteristics of its training data.
It is not a knowledge base. Always keep a human in the loop for consequential use.

---

## License & attribution

This model is a **Derivative Work** of Google **Gemma 4**, which Google releases under the
**Apache License 2.0** (see the official [Gemma 4 license](https://ai.google.dev/gemma/apache_2)).
AileyCore-12B is therefore also distributed under **Apache 2.0**.

In accordance with Apache 2.0 §4:

- The base Gemma 4 weights were **modified** via DoRA/LoRA adaptation and merged. Modified
  components are noted in `AILEY_MERGE_INFO.json` and this model card.
- A copy of the Apache 2.0 license is included (`LICENSE`).
- Attribution notices are provided in `NOTICE`.

Gemma is a trademark of Google LLC. This project is independent and **not** endorsed by or
affiliated with Google. Use of the name "Gemma" here is solely to describe the origin of the base model.

```
Copyright 2026 OpenM!nded / Simon van de Loo
Portions © Google LLC (Gemma 4), Apache License 2.0

Licensed under the Apache License, Version 2.0.
You may obtain a copy of the License at
    http://www.apache.org/licenses/LICENSE-2.0
```

## Citation

```bibtex
@misc{aileycore12b_2026,
  title  = {AileyCore-12B: A Gemma 4 fine-tune for the A!ley assistant},
  author = {van de Loo, Simon and OpenM!nded},
  year   = {2026},
  note   = {Fine-tuned and merged from Google Gemma 4 12B-IT (Apache 2.0)}
}
```