Instructions to use GhostScientist/semanticwiki-coder-7b-v2-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 GhostScientist/semanticwiki-coder-7b-v2-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 GhostScientist/semanticwiki-coder-7b-v2-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf GhostScientist/semanticwiki-coder-7b-v2-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 GhostScientist/semanticwiki-coder-7b-v2-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf GhostScientist/semanticwiki-coder-7b-v2-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 GhostScientist/semanticwiki-coder-7b-v2-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf GhostScientist/semanticwiki-coder-7b-v2-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 GhostScientist/semanticwiki-coder-7b-v2-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf GhostScientist/semanticwiki-coder-7b-v2-gguf:Q4_K_M

Use Docker

docker model run hf.co/GhostScientist/semanticwiki-coder-7b-v2-gguf:Q4_K_M

LM Studio
Jan

vLLM

How to use GhostScientist/semanticwiki-coder-7b-v2-gguf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "GhostScientist/semanticwiki-coder-7b-v2-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": "GhostScientist/semanticwiki-coder-7b-v2-gguf",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/GhostScientist/semanticwiki-coder-7b-v2-gguf:Q4_K_M

Ollama
How to use GhostScientist/semanticwiki-coder-7b-v2-gguf with Ollama:
```
ollama run hf.co/GhostScientist/semanticwiki-coder-7b-v2-gguf:Q4_K_M
```
Unsloth Desktop

How to use GhostScientist/semanticwiki-coder-7b-v2-gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf GhostScientist/semanticwiki-coder-7b-v2-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": "GhostScientist/semanticwiki-coder-7b-v2-gguf:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use GhostScientist/semanticwiki-coder-7b-v2-gguf with Docker Model Runner:
```
docker model run hf.co/GhostScientist/semanticwiki-coder-7b-v2-gguf:Q4_K_M
```

Lemonade

How to use GhostScientist/semanticwiki-coder-7b-v2-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull GhostScientist/semanticwiki-coder-7b-v2-gguf:Q4_K_M

Run and chat with the model

lemonade run user.semanticwiki-coder-7b-v2-gguf-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use GhostScientist/semanticwiki-coder-7b-v2-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 GhostScientist/semanticwiki-coder-7b-v2-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 GhostScientist/semanticwiki-coder-7b-v2-gguf:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use GhostScientist/semanticwiki-coder-7b-v2-gguf with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf GhostScientist/semanticwiki-coder-7b-v2-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 "GhostScientist/semanticwiki-coder-7b-v2-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"

SemanticWiki Coder 7B v2 — GGUF Q4_K_M

What?

This is the GGUF Q4_K_M quantization of GhostScientist/semanticwiki-coder-7b-v2-merged. It is intended for llama.cpp-compatible tools, including local desktop applications and browser-based interfaces backed by a local llama.cpp server.

The quantized file is approximately 4.46 GB. The original merged F16 GGUF is approximately 15.2 GB and was used as the quantization input.

Why?

GGUF is a convenient distribution format for local inference because it keeps model tensors and runtime metadata together and is supported by llama.cpp. Q4_K_M is a practical quality/size compromise for consumer hardware.

GGUF is a model format, not automatically an in-browser runtime. The most reliable browser workflow is to run llama-server locally and open its WebUI. Direct WebGPU/WebAssembly browser loading is a separate compatibility path and depends on the browser, device memory, and runtime build.

Quick start with llama.cpp

hf download GhostScientist/semanticwiki-coder-7b-v2-gguf \
  --include '*.gguf' \
  --local-dir ./semanticwiki-coder-7b-v2-gguf

llama-server \
  -m ./semanticwiki-coder-7b-v2-gguf/semanticwiki-coder-7b-v2-q4_k_m.gguf \
  -c 8192

Open the local URL printed by llama-server.

For a command-line smoke test:

llama-cli \
  -m ./semanticwiki-coder-7b-v2-gguf/semanticwiki-coder-7b-v2-q4_k_m.gguf \
  -p '<START_OF_CONTEXT>\nclass Greeter:\n    def hello(self):\n        return "hello"\n<END_OF_CONTEXT>\n\n<query>\nExplain this code.\n</query>' \
  -n 256