Instructions to use 0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-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 0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-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 0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF:UD-Q5_K_XL
# Run inference directly in the terminal:
llama cli -hf 0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF:UD-Q5_K_XL

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf 0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF:UD-Q5_K_XL
# Run inference directly in the terminal:
llama cli -hf 0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF:UD-Q5_K_XL

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf 0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF:UD-Q5_K_XL
# Run inference directly in the terminal:
./build/bin/llama cli -hf 0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF:UD-Q5_K_XL

Use Docker

docker model run hf.co/0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF:UD-Q5_K_XL

Llama new
LM Studio
Jan
Ollama
How to use 0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF with Ollama:
```
ollama run hf.co/0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF:UD-Q5_K_XL
```
Unsloth Desktop

How to use 0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf 0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF:UD-Q5_K_XL

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": "0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF:UD-Q5_K_XL"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use 0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF with Docker Model Runner:
```
docker model run hf.co/0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF:UD-Q5_K_XL
```

Lemonade

How to use 0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull 0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF:UD-Q5_K_XL

Run and chat with the model

lemonade run user.Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF-UD-Q5_K_XL

List all available models

lemonade list

Hermes Agent

How to use 0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-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 0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF:UD-Q5_K_XL

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 0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF:UD-Q5_K_XL

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use 0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf 0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF:UD-Q5_K_XL

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 "0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF:UD-Q5_K_XL" \
  --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"

Muse-Glimmer-30B-Heretic UD-Q5_K_XL GGUF

This repository contains one GGUF quantization of Muse-Glimmer-30B-Heretic. It was quantized directly from the Heretic BF16 GGUF using a new importance matrix calculated on that BF16 model. No Q8 intermediate was used.

The tensor types match Unsloth's Muse-Glimmer UD-Q5_K_XL tensor by tensor: 104 Q5_K, 150 Q6_K, 164 Q8_0, and 313 F32 tensors. Calibration used 166 chunks of 512 tokens from the bartowski imatrix corpus.

File	Size	SHA256
`Muse-Glimmer-30B-Heretic-UD-Q5_K_XL.gguf`	21.79 GB	`74e3fb3995cf9ce906ff809c55f426b97dae2cd46c87c4b04100813adb73cb0b`

hf download 0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF Muse-Glimmer-30B-Heretic-UD-Q5_K_XL.gguf
llama-cli -m Muse-Glimmer-30B-Heretic-UD-Q5_K_XL.gguf -ngl 99

The Heretic model was created by darkc0de from Meta's Muse-Glimmer-30B. This release follows the upstream Apache 2.0 license.

Downloads last month: 92

GGUF

Model size

28B params

Architecture

muse-glimmer

Hardware compatibility

5-bit

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Model tree for 0ppxnhximxr/Muse-Glimmer-30B-Heretic-UD-Q5_K_XL-GGUF

Base model

darkc0de/Muse-Glimmer-30B-heretic

Quantized

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