GPT_OSS_20B_ArduinoExpert_v4_GGUF

🤖 GPT_OSS_20B_ArduinoExpert_v0.2 - GGUF

Languages: 🇺🇸 English | 🇮🇹 Italiano | 🇫🇷 Français | 🇪🇸 Español | 🇩🇪 Deutsch

This model was finetuned and converted to GGUF format using Unsloth.

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🇬🇧 English Description

GPT_OSS_20B_ArduinoExpert_v0.2 is a specialized fine-tune designed to assist makers, students, and engineers with Arduino prototyping, embedded C++ programming, and circuit design.

🌍 Multilingual Capabilities

While fine-tuned primarily on English and Italian technical data, this model inherits the strong multilingual capabilities of the base gpt-oss-20b. It can understand and generate technical explanations in French, Spanish, and German, effectively bridging the gap between technical English documentation and your native language.

🚀 Capabilities

• Arduino/C++ Syntax: Modern libraries, proper memory management, and ISRs.
• Hardware Wiring: Pinouts for Arduino Uno, Nano, ESP32, and common sensor connections.
• Debugging: Identifying compilation errors and common hardware pitfalls.

⚠️ Limitations & Safety

• Voltage Logic: Always verify pin voltages (3.3V vs 5V) with a multimeter.
• Safety: Do NOT use for mains voltage (110V/220V).
• Hallucinations: Always check official datasheets.

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🇮🇹 Descrizione Italiana

GPT_OSS_20B_ArduinoExpert_v0.2 è un modello specializzato per Arduino, C++ embedded e progettazione circuitale.

🌍 Supporto Multilingue

Oltre all'Italiano e all'Inglese, il modello mantiene le capacità multilingue native di gpt-oss-20b. Puoi fargli domande in Francese, Spagnolo o Tedesco e ricevere risposte tecniche coerenti e codice commentato correttamente.

🚀 Cosa sa fare

• Codice C++: Scrive sketch ottimizzati per Arduino e ESP32.
• Hardware: Spiega come collegare sensori (I2C, SPI) e gestisce i pinout.
• Debug: Analizza errori di compilazione e suggerisce fix hardware.

⚠️ Avvertenze

1. Voltaggi: Controlla sempre i voltaggi col multimetro prima di collegare.
2. Sicurezza: Non usare per progetti ad alta tensione (220V).

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📂 Available Model Files / File Disponibili

🔧 Training Details

• Finetuned with: Unsloth
• Base Model: openai/gpt-oss-20b
• Format: GGUF

<br> <details> <summary><strong>📚 Citation / Citazione (Click to expand)</strong></summary>

@misc{unsloth2023,
    title={Unsloth: Faster and Memory Efficient LLM Fine-tuning},
    author={Daniel Han and Unsloth Team},
    year={2023},
    url={[https://github.com/unslothai/unsloth](https://github.com/unslothai/unsloth)}
}