socratic-gemma-4-it

🧠 Socratic-Gemma-4-IT (E2B) - Prevolut Ltd

This is a highly optimized, fine-tuned version of Google's Gemma 4 E2B IT (Edge 2B), developed and trained by Prevolut Ltd.

We engineered this model to bridge the gap between lightweight edge-computing and advanced structural reasoning. By utilizing a socratic fine-tuning approach (including high-quality datasets like GSM8K), this model excels at deterministic formatting, logical sequence tracking, and flawless tool orchestration.

🎯 Key Features & Enhancements

• Socratic Reasoning Engine: Instead of guessing answers, the model is trained to break down complex, multi-stage system problems step-by-step, running internal plausibility checks before outputting the final result.
• Format & Syntax Discipline: Highly disciplined in maintaining strict output structures. It isolates mathematical formulas cleanly and is exceptionally stable at generating pure JSON blocks without conversational clutter.
• MCP & Tool Orchestration Ready: Due to its strict formatting adherence, this model is an ideal candidate for serving as a local agent interacting with the Model Context Protocol (MCP), executing API calls, and managing local system states (e.g., Docker, databases).
• Multilingual Capability: Fully capable of reasoning and conversing in English, German, and French.
• Edge Optimized: Exported in the highly efficient Q4_K_M GGUF format, ensuring lightning-fast inference on local workstations, mobile environments, and consumer hardware.

💻 Intended Use Cases

1. Local AI Agents: Powering privacy-first, on-device assistants.
2. System Orchestration: Translating natural language into structured JSON payloads for tool execution.
3. Complex Logic Tasks: Solving riddles, dynamic queue simulations, and multi-variable logic puzzles.

🛠️ Technical Specifications

• Base Model: google/gemma-4-E2B-it
• Architecture: 2 Billion Parameters (Edge-optimized)
• Format: GGUF (Q4_K_M quantization)
• License: Apache 2.0 (Fully cleared for commercial use)

🚀 How to use

You can load this model directly into standard local inference tools such as LM Studio, Ollama, or any application built on top of llama.cpp.

Example Prompt for Tool Execution

To leverage the model's structural discipline for tool calls, we recommend enforcing markdown code blocks in your system prompts:

You are a local system agent. If you need to use a tool, output ONLY a valid JSON block inside markdown formatting. Do not add any conversational text before or after the JSON.

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Developed with focus on local AI efficiency by Prevolut Ltd