EleMo-Alpha-1-Base

<div align="center"> <h1>🧸 EleMo-Alpha-1 (Base Model)</h1> <h3>Status: Alpha-Release (Proof of Concept)</h3> </div>

About EleMo-Alpha-1

EleMo (Elementary Pedagogical Model) is a highly specialized, locally deployable Large Language Model (LLM) tailored exactly to the requirements of early childhood education. The objective: To relieve pedagogical professionals of documentation duties without transmitting sensitive developmental data of children to external clouds.

This repository contains the Alpha-1-Base-Version.

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💾 GGUF Variants for LM Studio & Local Usage

For deployment in LM Studio, Ollama, or other local inference engines, quantized GGUF variants are available. These enable operation on your own hardware, strictly adhering to the Zero-Cloud-Guarantee.

Find all GGUF model variants (Q4, Q6, Q8) here: 👉 EleMo-Alpha-1 GGUF Repository

• Q4_K_M: Recommended for efficient operation on systems with 16GB RAM/VRAM.
• Q8_0: Maximum precision for high-end workstations.

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🎯 Pedagogical Focus

EleMo is fine-tuned to transform raw observation data into structured Learning Stories, based on the methodological framework of Margaret Carr.

• Objectivity: Focus on description, not interpretation or evaluation (no armchair psychology).
• Structure: Observation – Significance – Next Steps (Opportunities).
• Tonality: Appreciative correspondence written directly to the child.

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💻 Hardware Requirements for GGUF Inference

Based on the Mistral-Small-24B architecture, we recommend the following hardware configurations for smooth inference:

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🖥️ How to use EleMo

To maintain your pedagogical data sovereignty, you can run EleMo locally using the LM Studio interface.

The Easy Way (GGUF Model)

If you want to start immediately without complex configurations:

1. Download: Go to the "Files and versions" tab and download the EleMo-Alpha-1.gguf file.
2. Open LM Studio: Launch the application on your local machine.
3. Load: Drag and drop the downloaded .gguf file directly into LM Studio.
4. Chat: Select the model in the chat interface and start your pedagogical documentation based on the Margaret Carr framework.

💡 Note: For advanced pedagogical fine-tuning or better performance with the EleMo-Adapter, please visit our ADAPTER-COLLECTION

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🛡️ Zero-Cloud-Guarantee

This model is designed for local data sovereignty. It does not rely on transmitting data to third-party servers. All pedagogical knowledge remains within your "KI-Insel" (AI Island), on your private server, or your local machine.

🔬 Access & Collaboration

As EleMo embodies deep-seated methodical knowledge of elementary pedagogy, access to the architecture is organized as a Private / Gated Model. To request access, please submit a request via the Hugging Face portal.

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<div align="center"> <p>— <b>Sebastian Götz</b> | Owner & Founder @ Kita Digital | Initiator of KI-Insel —</p> </div>