Instructions to use microtensor-io/baseline-front-text2sql-mt16g with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use microtensor-io/baseline-front-text2sql-mt16g 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 microtensor-io/baseline-front-text2sql-mt16g
# Run inference directly in the terminal:
llama cli -hf microtensor-io/baseline-front-text2sql-mt16g

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf microtensor-io/baseline-front-text2sql-mt16g
# Run inference directly in the terminal:
llama cli -hf microtensor-io/baseline-front-text2sql-mt16g

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 microtensor-io/baseline-front-text2sql-mt16g
# Run inference directly in the terminal:
./llama-cli -hf microtensor-io/baseline-front-text2sql-mt16g

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 microtensor-io/baseline-front-text2sql-mt16g
# Run inference directly in the terminal:
./build/bin/llama-cli -hf microtensor-io/baseline-front-text2sql-mt16g

Use Docker

docker model run hf.co/microtensor-io/baseline-front-text2sql-mt16g

LM Studio
Jan
Ollama
How to use microtensor-io/baseline-front-text2sql-mt16g with Ollama:
```
ollama run hf.co/microtensor-io/baseline-front-text2sql-mt16g
```
Unsloth Desktop

How to use microtensor-io/baseline-front-text2sql-mt16g with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf microtensor-io/baseline-front-text2sql-mt16g

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": "microtensor-io/baseline-front-text2sql-mt16g"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use microtensor-io/baseline-front-text2sql-mt16g with Docker Model Runner:
```
docker model run hf.co/microtensor-io/baseline-front-text2sql-mt16g
```

Lemonade

How to use microtensor-io/baseline-front-text2sql-mt16g with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull microtensor-io/baseline-front-text2sql-mt16g

Run and chat with the model

lemonade run user.baseline-front-text2sql-mt16g-{{QUANT_TAG}}

List all available models

lemonade list

Hermes Agent

How to use microtensor-io/baseline-front-text2sql-mt16g with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf microtensor-io/baseline-front-text2sql-mt16g

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 microtensor-io/baseline-front-text2sql-mt16g

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use microtensor-io/baseline-front-text2sql-mt16g with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf microtensor-io/baseline-front-text2sql-mt16g

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 "microtensor-io/baseline-front-text2sql-mt16g" \
  --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"

Front baseline

Qwen/Qwen3.5-9B at Q4_K_M, published front baseline for Microtensor subnet 92.

Downloads last month: 20

GGUF

Model size

9B params

Architecture

qwen35

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 microtensor-io/baseline-front-text2sql-mt16g

Base model

Qwen/Qwen3.5-9B-Base

Finetuned

Qwen/Qwen3.5-9B

Quantized

(582)

this model