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Titaniumclock/Gemma-4-Rust-Coder

sourceHugging Facemitupdated 4mo agoView on Hugging Face

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Model Card

Gemma-4-Rust-Coder : GGUF

This model is a specialized fine-tune of Gemma 4, specifically optimized for Rust systems programming, memory safety patterns, and high-performance development. It was trained using Unsloth Studio to ensure maximum efficiency and performance.

🦀 Fine-Tuning Focus

The model has been adjusted to excel in:

—Idiomatic Rust: Writing clean, "Rusty" code using modern patterns.
—Concurrency: Deep understanding of Send, Sync, and async runtimes like Tokio.
—Vision-to-Code: Using its multimodal capabilities to translate architecture diagrams or UI mockups into functional Rust code.

🤝 Credits & Acknowledgments

Special thanks to Fortytwo-Network for providing the [Strandset-Rust-v1](https://huggingface.co/datasets/Fortytwo-Network/Strandset-Rust-v1) dataset. This model's specialized knowledge of the Rust ecosystem is a direct result of this high-quality data.

🚀 Usage

This model is converted to GGUF format for seamless use with llama.cpp and other compatible executors.

Example usage:

—Text-only LLM: llama-cli -hf MassivDash/Gemma-4-Rust-Coder --jinja
—Multimodal / Vision: llama-mtmd-cli -hf MassivDash/Gemma-4-Rust-Coder --jinja

📂 Available Model files:

—gemma-4-e2b-it.Q3_K_M.gguf
—gemma-4-e2b-it.BF16-mmproj.gguf

⚠️ Ollama Note for Vision Models

Important: Ollama currently does not support separate mmproj files for vision models.

To create an Ollama model from this vision model:

1.Place the Modelfile in the same directory as the finetuned bf16 merged model.
2.Run: ollama create model_name -f ./Modelfile (Replace `model_name` with your desired name)

🔗 Stay Connected

For more insights on AI development and fine-tuning, visit my blog: 👉 [spaceout.pl](https://spaceout.pl)

This model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth)