Instructions to use sylvester-francis/rust-mentor-1.7b-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use sylvester-francis/rust-mentor-1.7b-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf sylvester-francis/rust-mentor-1.7b-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf sylvester-francis/rust-mentor-1.7b-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf sylvester-francis/rust-mentor-1.7b-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf sylvester-francis/rust-mentor-1.7b-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf sylvester-francis/rust-mentor-1.7b-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf sylvester-francis/rust-mentor-1.7b-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf sylvester-francis/rust-mentor-1.7b-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf sylvester-francis/rust-mentor-1.7b-GGUF:Q4_K_M

Use Docker

docker model run hf.co/sylvester-francis/rust-mentor-1.7b-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use sylvester-francis/rust-mentor-1.7b-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "sylvester-francis/rust-mentor-1.7b-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "sylvester-francis/rust-mentor-1.7b-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/sylvester-francis/rust-mentor-1.7b-GGUF:Q4_K_M

Ollama
How to use sylvester-francis/rust-mentor-1.7b-GGUF with Ollama:
```
ollama run hf.co/sylvester-francis/rust-mentor-1.7b-GGUF:Q4_K_M
```
Unsloth Desktop

How to use sylvester-francis/rust-mentor-1.7b-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf sylvester-francis/rust-mentor-1.7b-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "sylvester-francis/rust-mentor-1.7b-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use sylvester-francis/rust-mentor-1.7b-GGUF with Docker Model Runner:
```
docker model run hf.co/sylvester-francis/rust-mentor-1.7b-GGUF:Q4_K_M
```

Lemonade

How to use sylvester-francis/rust-mentor-1.7b-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull sylvester-francis/rust-mentor-1.7b-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.rust-mentor-1.7b-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use sylvester-francis/rust-mentor-1.7b-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf sylvester-francis/rust-mentor-1.7b-GGUF:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default sylvester-francis/rust-mentor-1.7b-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use sylvester-francis/rust-mentor-1.7b-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf sylvester-francis/rust-mentor-1.7b-GGUF:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "sylvester-francis/rust-mentor-1.7b-GGUF:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

RustMentor-1.7B-GGUF

RustMentor-1.7B-GGUF is a 1.7B-parameter Qwen3-based model fine-tuned for Rust programming education and code review. It merges the base model with LoRA adapters and includes GGUF quantization for local/mobile/Ollama workflows.

This repository hosts the GGUF quantized model (Q4_K_M) for lightweight inference. For the LoRA adapter, see rust-mentor-1.7b.

Model Description

Base Model: Qwen/Qwen3-1.7B
Model Type: Causal LM (code tutoring + review)
Parameters: 1.7B
Context Length: 2048 tokens
Fine-tuning: QLoRA (r=16, alpha=16) with Unsloth optimization
Quantization: Q4_K_M (~1.1GB)
License: Apache 2.0
Language: English, Rust code
System Prompt: Rust programming tutor for experienced Go/Python/TypeScript developers learning Rust by building CLI tools.

What It Is Good At

Explaining 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 and Tokio patterns
Smart pointers (Box, Rc, Arc, RefCell)
Pattern matching and enum-based design
Trait-based architecture and generics
Type conversions (From, Into, AsRef, Deref)
Serde & JSON serialization
CLI tooling with clap
Cargo project structure, modules, and workspaces
Testing patterns and documentation

Intended Uses

Primary: Offline Rust programming tutor on Android (Pixel 8 Pro tested) via PocketPal AI, or local inference via Ollama/llama.cpp.

Out-of-scope: General-purpose chat, non-Rust programming, safety-sensitive or factual tasks outside Rust development.

Prompt Examples

"In Go, I just pass values or pointers. What's this ownership thing in Rust?"

"Review this Rust code and explain what the borrow checker is doing:\n\nfn get_longest(a: String, b: String) -> String {\n    if a.len() > b.len() { a } else { b }\n}"

"How do I handle errors in Rust? I'm used to Go's if err != nil pattern."

"How does async work in Rust? In Go I just use goroutines and it's simple."

How to Use

PocketPal AI (Android — Offline)

Install PocketPal AI from Play Store
Tap "Add from Hugging Face"
Search: sylvester-francis/rust-mentor-1.7b-GGUF
Download the Q4_K_M quantization (~1.1GB)
Create a "Pal" with the Rust tutor system prompt
Enable airplane mode and start learning!

Ollama (Local)

# Download the GGUF
huggingface-cli download sylvester-francis/rust-mentor-1.7b-GGUF \
  --local-dir ./models/rust-mentor

# Create Modelfile
cat > Modelfile << 'MODELFILE'
FROM ./models/rust-mentor/<gguf-filename>.gguf

SYSTEM """You are RustMentor, an expert Rust programming tutor. The student is an experienced Go, Python, and TypeScript developer learning Rust by building CLI tools. Draw parallels to Go/Python/TypeScript concepts. Explain ownership, borrowing, and lifetimes with practical examples."""

PARAMETER temperature 0.7
PARAMETER top_p 0.9
PARAMETER num_ctx 2048
MODELFILE

ollama create rust-mentor -f Modelfile
ollama run rust-mentor "Explain Rust's ownership vs Go's garbage collector"

llama.cpp

huggingface-cli download sylvester-francis/rust-mentor-1.7b-GGUF \
  --local-dir ./models

./llama-cli -m ./models/<gguf-filename>.gguf \
  -p "Explain and fix this Rust borrow checker error..."

Training Data (Summary)

Strandset-Rust-v1: 3,000 samples of Rust code generation, review, refactoring, and bug detection tasks
Synthetic tutor conversations: 46 unique hand-crafted Rust tutoring dialogues across 28 topics, covering ownership, error handling, traits, async, smart pointers, macros, serde, testing, and more
Style: All conversations draw parallels to Go/Python/TypeScript equivalents

Training Configuration (QLoRA)

Parameter	Value
Base Model	Qwen/Qwen3-1.7B
Method	QLoRA via Unsloth
LoRA Rank (r)	16
LoRA Alpha	16
Target Modules	q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
Epochs	3
Batch Size	2 x 4 (effective 8)
Learning Rate	2e-4 (cosine schedule)
Max Sequence Length	2048
Hardware	NVIDIA A100 40GB (Google Colab)

Evaluation

Qualitative checks on Rust tutoring prompts show:

Clear explanations with Go/Python/TypeScript comparisons
Accurate code examples with proper ownership and borrowing
Borrow checker explanations in code reviews
Appropriate use of idiomatic Rust patterns

Safety & Limitations

May generate incorrect code or hallucinate crate APIs — review before production use.
Not a replacement for the Rust compiler or clippy — always compile and test generated code.
Optimized for tutoring, not production code generation at scale.
Training data focuses on CLI/systems patterns; web framework coverage (Axum, Actix) is limited.

License

Apache 2.0 for the fine-tuned model; base model (Qwen/Qwen3-1.7B) license also applies.

Contact

Maintainer: Sylvester Francis (@sylvester-francis)
Repository: github.com/sylvester-francis/slm-rust-model
Issues/feedback: Open a discussion on the model repo

Downloads last month: 68

GGUF

Model size

2B params

Architecture

qwen3

Hardware compatibility

4-bit

Model tree for sylvester-francis/rust-mentor-1.7b-GGUF

Base model

Qwen/Qwen3-1.7B-Base

Finetuned

Qwen/Qwen3-1.7B

Quantized

(353)

this model

sylvester-francis
/

rust-mentor-1.7b-GGUF

RustMentor-1.7B-GGUF

Model Description

What It Is Good At

Intended Uses

Prompt Examples

How to Use

PocketPal AI (Android — Offline)

Ollama (Local)

llama.cpp

Training Data (Summary)

Training Configuration (QLoRA)

Evaluation

Safety & Limitations

License

Contact

Model tree for sylvester-francis/rust-mentor-1.7b-GGUF

Dataset used to train sylvester-francis/rust-mentor-1.7b-GGUF