val options = LlmInferenceOptions.builder()
    .setModelPath("/path/to/rust_mentor_1b_mobile.litertlm")
    .setMaxTokens(512)
    .build()
val llm = LlmInference.createFromOptions(context, options)
val response = llm.generateResponse("Explain Rust ownership to a Go developer")

What It Does

Explains Rust ownership, borrowing, and lifetimes with Go/Python/TS comparisons
Code review with borrow checker explanations
Error handling patterns (Result, Option, ?, thiserror, anyhow)
Async/await, smart pointers, pattern matching, traits
CLI tooling with clap, Cargo project structure

Training Data

Strandset-Rust-v1: 3,000 samples of Rust code tasks
Synthetic tutor conversations: 46 hand-crafted dialogues across 28 topics
Style: Draws parallels to Go/Python/TypeScript

Training Configuration

Parameter	Value
Base Model	google/gemma-3-1b-it
Method	QLoRA via Unsloth
LoRA Rank	16
Epochs	3
Effective Batch Size	8
Learning Rate	2e-4 (cosine)

Export Configuration

Parameter	Value
Converter	litert-torch (Gemma3 built-in)
Quantization	Dynamic INT8
KV Cache	2048
Format	.litertlm
GPU Delegation	Full on Tensor G3

Safety & Limitations

May generate incorrect code — always compile and test
Optimized for tutoring, not production code generation
Training data focuses on CLI/systems patterns

License

Gemma license — free for commercial use. See Gemma Terms.

Contact

Maintainer: Sylvester Francis
Repository: github.com/sylvester-francis/slm-rust-model

sylvester-francis/rust-mentor-1b-mobile-LiteRT

RustMentor 1B Mobile — LiteRT

Model Description

How to Use

Google AI Edge Gallery (Android)

LiteRT-LM (Kotlin)

What It Does

Training Data

Training Configuration

Export Configuration

Safety & Limitations

License

Contact

sylvester-francis/
rust-mentor-1b-mobile-LiteRT