Instructions to use zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-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 zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-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 zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-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 zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-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 zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF:Q4_K_M

Use Docker

docker model run hf.co/zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-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": "zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF:Q4_K_M

SGLang

How to use zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF with Ollama:
```
ollama run hf.co/zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF:Q4_K_M
```

Unsloth Studio

How to use zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF to start chatting

How to use zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF: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 "zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF: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"

Docker Model Runner
How to use zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF with Docker Model Runner:
```
docker model run hf.co/zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF:Q4_K_M
```

Lemonade

How to use zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-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 zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF: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 zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

You need to read and agree to the Disclaimer and User Agreementa to access this model.

Disclaimer and User Agreement

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If you do not agree with any part of this Agreement, do not request or use the Model.

Nature of the Model & Risk Notice
The Model is trained using large-scale machine learning techniques and may generate inaccurate, false, offensive, violent, sexual, discriminatory, politically sensitive, or otherwise uncontrolled content.

The Model does not guarantee the accuracy, completeness, or legality of any generated content. You must independently evaluate and verify the outputs, and you assume all risks arising from their use.

The Model may reflect biases or errors present in its training data, potentially producing inappropriate or controversial outputs.

License and Permitted Use
You may use the Model solely for lawful, compliant, and non-malicious purposes in research, learning, experimentation, and development, in accordance with applicable laws and regulations.

You must not use the Model for activities including, but not limited to:

Creating, distributing, or promoting unlawful, violent, pornographic, terrorist, discriminatory, defamatory, or privacy-invasive content;

Any activity that could cause significant negative impact on individuals, groups, organizations, or society;

High-risk applications such as automated decision-making, medical diagnosis, financial transactions, or legal advice without proper validation and human oversight.

You must not remove, alter, or circumvent any safety mechanisms implemented in the Model.

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You are solely responsible for any data processed or generated when using the Model, including compliance with data protection and privacy regulations.

The Model’s authors and contributors make no guarantees or warranties regarding data security or privacy.

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You agree to bear full legal responsibility for any disputes, claims, or litigation arising from your use of the Model, and you release the authors and contributors from any related liability.

Updates and Termination
This Agreement may be updated at any time, with updates posted on the Model’s page and effective immediately upon publication.

If you violate this Agreement, the authors reserve the right to revoke your access to the Model at any time.

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zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF

This model was converted to GGUF format from Jinx-org/Jinx-Qwen3-30B-A3B-Thinking-2507 using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

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.

CLI:

llama-cli --hf-repo zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF --hf-file jinx-qwen3-30b-a3b-thinking-2507-q4_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF --hf-file jinx-qwen3-30b-a3b-thinking-2507-q4_k_m.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF --hf-file jinx-qwen3-30b-a3b-thinking-2507-q4_k_m.gguf -p "The meaning to life and the universe is"

./llama-server --hf-repo zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF --hf-file jinx-qwen3-30b-a3b-thinking-2507-q4_k_m.gguf -c 2048

Downloads last month: -

GGUF

Model size

31B params

Architecture

qwen3moe

Hardware compatibility

4-bit

Model tree for zehuajun/Jinx-Qwen3-30B-A3B-Thinking-2507-Q4_K_M-GGUF

Base model

Qwen/Qwen3-30B-A3B-Thinking-2507

Finetuned

Jinx-org/Jinx-Qwen3-30B-A3B-Thinking-2507

Quantized

(9)

this model