fabxx48/GPT_OSS_20B_ArduinoExpert_v4_GGUF
๐ค GPTOSS20BArduinoExpertv0.2 - GGUF
Languages: ๐บ๐ธ English | ๐ฎ๐น Italiano | ๐ซ๐ท Franรงais | ๐ช๐ธ Espaรฑol | ๐ฉ๐ช Deutsch This model was finetuned and converted to GGUF format using Unsloth.
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๐ฌ๐ง 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.
๐ 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.
๐ 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.
โ ๏ธ 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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๐ฎ๐น Descrizione Italiana
GPT_OSS_20B_ArduinoExpert_v0.2 รจ un modello specializzato per Arduino, C++ embedded e progettazione circuitale.
๐ Supporto Multilingue
Oltre all'Italiano e all'Inglese, il modello mantiene le capacitร multilingue native di gpt-oss-20b. Puoi fargli domande in Francese, Spagnolo o Tedesco e ricevere risposte tecniche coerenti e codice commentato correttamente.
๐ 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.
โ ๏ธ Avvertenze
- Voltaggi: Controlla sempre i voltaggi col multimetro prima di collegare.
- Sicurezza: Non usare per progetti ad alta tensione (220V).
๐ Available Model Files / File Disponibili
๐ง Training Details
- Finetuned with: Unsloth
- Base Model: openai/gpt-oss-20b
- Format: GGUF
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<details> <summary><strong>๐ 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)}
}