Instructions to use Kj0rdan/gguf-ggml-model-mirror with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use Kj0rdan/gguf-ggml-model-mirror 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 Kj0rdan/gguf-ggml-model-mirror:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Kj0rdan/gguf-ggml-model-mirror:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Kj0rdan/gguf-ggml-model-mirror:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Kj0rdan/gguf-ggml-model-mirror: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 Kj0rdan/gguf-ggml-model-mirror:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Kj0rdan/gguf-ggml-model-mirror: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 Kj0rdan/gguf-ggml-model-mirror:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Kj0rdan/gguf-ggml-model-mirror:Q4_K_M

Use Docker

docker model run hf.co/Kj0rdan/gguf-ggml-model-mirror:Q4_K_M

LM Studio
Jan
Ollama
How to use Kj0rdan/gguf-ggml-model-mirror with Ollama:
```
ollama run hf.co/Kj0rdan/gguf-ggml-model-mirror:Q4_K_M
```
Unsloth Desktop

How to use Kj0rdan/gguf-ggml-model-mirror with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Kj0rdan/gguf-ggml-model-mirror: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": "Kj0rdan/gguf-ggml-model-mirror:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use Kj0rdan/gguf-ggml-model-mirror with Docker Model Runner:
```
docker model run hf.co/Kj0rdan/gguf-ggml-model-mirror:Q4_K_M
```

Lemonade

How to use Kj0rdan/gguf-ggml-model-mirror with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Kj0rdan/gguf-ggml-model-mirror:Q4_K_M

Run and chat with the model

lemonade run user.gguf-ggml-model-mirror-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use Kj0rdan/gguf-ggml-model-mirror with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Kj0rdan/gguf-ggml-model-mirror: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 Kj0rdan/gguf-ggml-model-mirror:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Kj0rdan/gguf-ggml-model-mirror with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Kj0rdan/gguf-ggml-model-mirror: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 "Kj0rdan/gguf-ggml-model-mirror: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"

GGUF / GGML model mirror

Byte-for-byte copies of four quantised models: two GGUF language models for llama.cpp and two GGML speech recognition models for whisper.cpp.

Nothing here is original work and nothing has been modified. Each file is a copy of the file named in the table below, mirrored so that a fixed set of weights stays available at a stable address. Upstream repositories get reorganised, re-quantised and occasionally deleted; a mirror pinned to a known checksum does not.

If you are choosing models to use, prefer the upstream repositories linked below — they are maintained, this is not.

Files

File	Size	Parameters	Quantisation
`Qwen3-1.7B-Q4_K_M.gguf`	1.03 GiB	1.7B	Q4_K_M
`Llama-3.2-3B-Instruct-Q4_K_M.gguf`	1.88 GiB	3.2B	Q4_K_M
`ggml-base.bin`	141 MiB	74M	float16
`ggml-tiny.bin`	74 MiB	39M	float16

Provenance and checksums

Copied 2026-08-30. Each file was verified against its SHA-256 after download and again after upload.

File	Copied from	SHA-256
`Qwen3-1.7B-Q4_K_M.gguf`	unsloth/Qwen3-1.7B-GGUF	`b139949c5bd74937ad8ed8c8cf3d9ffb1e99c866c823204dc42c0d91fa181897`
`Llama-3.2-3B-Instruct-Q4_K_M.gguf`	bartowski/Llama-3.2-3B-Instruct-GGUF	`6c1a2b41161032677be168d354123594c0e6e67d2b9227c84f296ad037c728ff`
`ggml-base.bin`	ggerganov/whisper.cpp	`60ed5bc3dd14eea856493d334349b405782ddcaf0028d4b5df4088345fba2efe`
`ggml-tiny.bin`	ggerganov/whisper.cpp	`be07e048e1e599ad46341c8d2a135645097a538221678b7acdd1b1919c6e1b21`

Credit for the quantisations and conversions belongs to their publishers: Qwen3 GGUF by unsloth, Llama 3.2 GGUF by bartowski, and the Whisper GGML conversions by Georgi Gerganov. The base weights are by Alibaba Cloud (Qwen3), Meta (Llama 3.2) and OpenAI (Whisper).

Licences

Three different licences apply, each only to its own files. See NOTICE for the attribution notices that must travel with these copies.

Qwen3-1.7B-Q4_K_M.gguf — Apache License 2.0, LICENSE-apache-2.0.txt.
Llama-3.2-3B-Instruct-Q4_K_M.gguf — Llama 3.2 Community License, LICENSE-llama-3.2.txt. Use is also governed by Meta's Acceptable Use Policy at https://www.llama.com/llama3_2/use-policy, which the licence incorporates by reference.

Built with Llama. Llama 3.2 is licensed under the Llama 3.2 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved.
ggml-base.bin, ggml-tiny.bin — MIT, LICENSE-mit.txt.

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GGUF

Model size

3B params

Architecture

llama

Hardware compatibility

4-bit

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