Instructions to use Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-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 Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-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 Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF
# Run inference directly in the terminal:
llama cli -hf Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF
# Run inference directly in the terminal:
llama cli -hf Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF

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 Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF
# Run inference directly in the terminal:
./llama-cli -hf Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF

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 Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF

Use Docker

docker model run hf.co/Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF

LM Studio
Jan

vLLM

How to use Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-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": "Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF

Ollama
How to use Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF with Ollama:
```
ollama run hf.co/Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF
```
Unsloth Desktop

How to use Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF

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": "Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF with Docker Model Runner:
```
docker model run hf.co/Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF
```

Lemonade

How to use Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF

Run and chat with the model

lemonade run user.DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF-{{QUANT_TAG}}

List all available models

lemonade list

Hermes Agent

How to use Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-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 Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF

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 Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF

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 "Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF" \
  --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"

What is that?

This is a mixed quantization of DarkArtsForge/Zepar-24B-v1 leveraging ik_llama.cpp SOTA quantization to compete with IQ4_XS mainline quants.
F16 GGUF and imatrix are avaliable here.

Quant Details

iq4_ks: ffn_gate, ffn_up, ffn_down, token_embd
iq5_ks: attn_q, attn_v, attn_k, attn_output
iq6_k: output
imatrix created based on calibration data by bartowski

quantized with ik_llama.cpp build: 9d07d868

incompatible with mainline llama.cpp
only tested with ik_llama.cpp (though I expect croco.cpp to work as well?)

Rationale

I wanted an "IQ4_XS but better" with ik_llama for personal use. I made it. WYSIWYG.

Cheers

MistralAI - the beloved base model(s).
ikawrakow and contributors of ik_llama.cpp - I probably misused your wonderful creation.
DarkArtsForge/Naphula - for the effort of designing and producing the merge. And for reviving my interest in Mistral 24b.
+++ Everyone whose finetunes were included in the merge!
bartowski - for the calibration data + the myriad of quants we all benefit from.

Disclosure

imatrix generated on an intermediary q8_0 quant. I don't eat RAM for breakfast.
My only contribution is compute. This is neither my merge, nor my calibration data. Have fun.

Downloads last month: 28

GGUF

Model size

24B params

Architecture

llama

Hardware compatibility

Model tree for Koshkasa/DarkArtsForge_Zepar-24B-v1-IQ4_KS-GGUF

Base model

DarkArtsForge/Zepar-24B-v1

Quantized

(7)

this model