Instructions to use Stephen123456/mt-s92-code-mt3g-qwen05-q4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use Stephen123456/mt-s92-code-mt3g-qwen05-q4 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 Stephen123456/mt-s92-code-mt3g-qwen05-q4
# Run inference directly in the terminal:
llama cli -hf Stephen123456/mt-s92-code-mt3g-qwen05-q4

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Stephen123456/mt-s92-code-mt3g-qwen05-q4
# Run inference directly in the terminal:
llama cli -hf Stephen123456/mt-s92-code-mt3g-qwen05-q4

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 Stephen123456/mt-s92-code-mt3g-qwen05-q4
# Run inference directly in the terminal:
./llama-cli -hf Stephen123456/mt-s92-code-mt3g-qwen05-q4

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 Stephen123456/mt-s92-code-mt3g-qwen05-q4
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Stephen123456/mt-s92-code-mt3g-qwen05-q4

Use Docker

docker model run hf.co/Stephen123456/mt-s92-code-mt3g-qwen05-q4

LM Studio
Jan
Ollama
How to use Stephen123456/mt-s92-code-mt3g-qwen05-q4 with Ollama:
```
ollama run hf.co/Stephen123456/mt-s92-code-mt3g-qwen05-q4
```
Unsloth Desktop

How to use Stephen123456/mt-s92-code-mt3g-qwen05-q4 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Stephen123456/mt-s92-code-mt3g-qwen05-q4

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": "Stephen123456/mt-s92-code-mt3g-qwen05-q4"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use Stephen123456/mt-s92-code-mt3g-qwen05-q4 with Docker Model Runner:
```
docker model run hf.co/Stephen123456/mt-s92-code-mt3g-qwen05-q4
```

Lemonade

How to use Stephen123456/mt-s92-code-mt3g-qwen05-q4 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Stephen123456/mt-s92-code-mt3g-qwen05-q4

Run and chat with the model

lemonade run user.mt-s92-code-mt3g-qwen05-q4-{{QUANT_TAG}}

List all available models

lemonade list

Hermes Agent

How to use Stephen123456/mt-s92-code-mt3g-qwen05-q4 with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Stephen123456/mt-s92-code-mt3g-qwen05-q4

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 Stephen123456/mt-s92-code-mt3g-qwen05-q4

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Stephen123456/mt-s92-code-mt3g-qwen05-q4 with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Stephen123456/mt-s92-code-mt3g-qwen05-q4

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 "Stephen123456/mt-s92-code-mt3g-qwen05-q4" \
  --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"

Microtensor Subnet 92 — code/mt-3g front (Q4_0)

LoRA fine-tuned Qwen2.5-Coder-0.5B for Microtensor subnet 92 code track.

Field	Value
Track	code
Class	mt-3g
Quant	q4_0
Base	Qwen/Qwen2.5-Coder-0.5B-Instruct@ea3f2471
Hotkey	5FjmWwbnPzVUYdFG8aDS14zdu2tzgMRmdtpdTmyaVBkAsGQD
Entrypoint	model.gguf

Downloads last month: 107

GGUF

Model size

0.5B params

Architecture

qwen2

Hardware compatibility

We're not able to determine the quantization variants.

View all variants

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for Stephen123456/mt-s92-code-mt3g-qwen05-q4

Base model

Qwen/Qwen2.5-0.5B

Finetuned

Qwen/Qwen2.5-Coder-0.5B

Finetuned

Qwen/Qwen2.5-Coder-0.5B-Instruct

Quantized

(84)

this model