Instructions to use KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I 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 KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I
# Run inference directly in the terminal:
llama cli -hf KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I
# Run inference directly in the terminal:
llama cli -hf KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I

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 KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I
# Run inference directly in the terminal:
./llama-cli -hf KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I

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 KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I
# Run inference directly in the terminal:
./build/bin/llama-cli -hf KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I

Use Docker

docker model run hf.co/KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I

LM Studio
Jan

vLLM

How to use KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I

Ollama
How to use KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I with Ollama:
```
ollama run hf.co/KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I
```
Unsloth Desktop

How to use KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I

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": "KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I with Docker Model Runner:
```
docker model run hf.co/KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I
```

Lemonade

How to use KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I

Run and chat with the model

lemonade run user.Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I-{{QUANT_TAG}}

List all available models

lemonade list

Hermes Agent

How to use KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I

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 KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I

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 "KaviarLabs/Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I" \
  --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"

K4viar commited on Jul 22

Commit

a91a6f0

verified ·

1 Parent(s): 9d9cb6a

Update model card for standardized GGUF filename

Browse files

Files changed (1) hide show

README.md +3 -3

README.md CHANGED Viewed

@@ -51,7 +51,7 @@ This source checkpoint contains a separate `output.weight`, resulting in 659 ten
 | File | Size | SHA-256 | Purpose |
 |---|---:|---|---|
-| `Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-PRO-DQ-IMATRIX.gguf` | 17.32 GiB | `7f556d9679961ddd25c2e51ed705e6152d8a395d97cdc013d7ada2fa8447ebc3` | Unofficial PRISM-PRO-DQ tensor-map reapplication with Unsloth I-matrix |
 ## Template and tokenizer
@@ -61,13 +61,13 @@ This source checkpoint contains a separate `output.weight`, resulting in 659 ten
 ## Usage with llama.cpp
 ```bash
-llama-cli -m Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-PRO-DQ-IMATRIX.gguf --jinja -p "Hello"
 ```
 For server use:
 ```bash
-llama-server -m Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-PRO-DQ-IMATRIX.gguf --jinja --host 127.0.0.1 --port 8080
 ```
 ## References

 | File | Size | SHA-256 | Purpose |
 |---|---:|---|---|
+| `Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I.gguf` | 17.32 GiB | `7f556d9679961ddd25c2e51ed705e6152d8a395d97cdc013d7ada2fa8447ebc3` | Unofficial PRISM-PRO-DQ tensor-map reapplication with Unsloth I-matrix |
 ## Template and tokenizer
 ## Usage with llama.cpp
 ```bash
+llama-cli -m Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I.gguf --jinja -p "Hello"
 ```
 For server use:
 ```bash
+llama-server -m Gemma-4-26B-A4B-Moonlight-Dusk-Heretic-PRISM-DQ-I.gguf --jinja --host 127.0.0.1 --port 8080
 ```
 ## References