Instructions to use IntelligentEstate/Tanngrisnir-Qwen3-4B-Q4_K_M-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 IntelligentEstate/Tanngrisnir-Qwen3-4B-Q4_K_M-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 IntelligentEstate/Tanngrisnir-Qwen3-4B-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf IntelligentEstate/Tanngrisnir-Qwen3-4B-Q4_K_M-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 IntelligentEstate/Tanngrisnir-Qwen3-4B-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf IntelligentEstate/Tanngrisnir-Qwen3-4B-Q4_K_M-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 IntelligentEstate/Tanngrisnir-Qwen3-4B-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf IntelligentEstate/Tanngrisnir-Qwen3-4B-Q4_K_M-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 IntelligentEstate/Tanngrisnir-Qwen3-4B-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf IntelligentEstate/Tanngrisnir-Qwen3-4B-Q4_K_M-GGUF:Q4_K_M

Use Docker

docker model run hf.co/IntelligentEstate/Tanngrisnir-Qwen3-4B-Q4_K_M-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use IntelligentEstate/Tanngrisnir-Qwen3-4B-Q4_K_M-GGUF with Ollama:
```
ollama run hf.co/IntelligentEstate/Tanngrisnir-Qwen3-4B-Q4_K_M-GGUF:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use IntelligentEstate/Tanngrisnir-Qwen3-4B-Q4_K_M-GGUF with Docker Model Runner:
```
docker model run hf.co/IntelligentEstate/Tanngrisnir-Qwen3-4B-Q4_K_M-GGUF:Q4_K_M
```

Lemonade

How to use IntelligentEstate/Tanngrisnir-Qwen3-4B-Q4_K_M-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull IntelligentEstate/Tanngrisnir-Qwen3-4B-Q4_K_M-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Tanngrisnir-Qwen3-4B-Q4_K_M-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

IntelligentEstate/Tanngrisnir-Qwen3-4B-Q4_K_M-GGUF

A small fast Goat further gnashed from Bunny's 4GB model

This model was converted to GGUF format from bunnycore/Qwen3-4B-Dot-Goat using llama.cpp

Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

Downloads last month: 17

GGUF

Model size

4B params

Architecture

qwen3

Hardware compatibility

4-bit

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Model tree for IntelligentEstate/Tanngrisnir-Qwen3-4B-Q4_K_M-GGUF

Base model

bunnycore/Qwen3-4B-Dot-Goat

Quantized

(3)

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