Instructions to use maylore-ai/Temper-2-Nodel-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 maylore-ai/Temper-2-Nodel-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 maylore-ai/Temper-2-Nodel-GGUF:BF16
# Run inference directly in the terminal:
llama cli -hf maylore-ai/Temper-2-Nodel-GGUF:BF16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf maylore-ai/Temper-2-Nodel-GGUF:BF16
# Run inference directly in the terminal:
llama cli -hf maylore-ai/Temper-2-Nodel-GGUF:BF16

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 maylore-ai/Temper-2-Nodel-GGUF:BF16
# Run inference directly in the terminal:
./build/bin/llama cli -hf maylore-ai/Temper-2-Nodel-GGUF:BF16

Use Docker

docker model run hf.co/maylore-ai/Temper-2-Nodel-GGUF:BF16

Llama new
LM Studio
Jan

vLLM

How to use maylore-ai/Temper-2-Nodel-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "maylore-ai/Temper-2-Nodel-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": "maylore-ai/Temper-2-Nodel-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/maylore-ai/Temper-2-Nodel-GGUF:BF16

Ollama
How to use maylore-ai/Temper-2-Nodel-GGUF with Ollama:
```
ollama run hf.co/maylore-ai/Temper-2-Nodel-GGUF:BF16
```
Unsloth Desktop

How to use maylore-ai/Temper-2-Nodel-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf maylore-ai/Temper-2-Nodel-GGUF:BF16

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": "maylore-ai/Temper-2-Nodel-GGUF:BF16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use maylore-ai/Temper-2-Nodel-GGUF with Docker Model Runner:
```
docker model run hf.co/maylore-ai/Temper-2-Nodel-GGUF:BF16
```

Lemonade

How to use maylore-ai/Temper-2-Nodel-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull maylore-ai/Temper-2-Nodel-GGUF:BF16

Run and chat with the model

lemonade run user.Temper-2-Nodel-GGUF-BF16

List all available models

lemonade list

Hermes Agent

How to use maylore-ai/Temper-2-Nodel-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 maylore-ai/Temper-2-Nodel-GGUF:BF16

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 maylore-ai/Temper-2-Nodel-GGUF:BF16

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use maylore-ai/Temper-2-Nodel-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf maylore-ai/Temper-2-Nodel-GGUF:BF16

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 "maylore-ai/Temper-2-Nodel-GGUF:BF16" \
  --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"

Temper-2-Nodel-GGUF

GGUF version of Temper-2-Nodel, a 4B model for Rust code. Results and details are on the main model page.

Website: maylore.com/temper-2-nodel

File	Quantization	Size
`Temper-2-Nodel-Q8_0.gguf`	Q8_0	4.48 GB
`Temper-2-Nodel-BF16.gguf`	BF16	8.42 GB

The recommended temperature is 0.2. The Modelfile and params in this repository set it for Ollama along with top_p 0.95, the settings of the published results.

llama.cpp

llama-cli -hf maylore-ai/Temper-2-Nodel-GGUF:Q8_0 --temp 0.2 --top-p 0.95

LM Studio

LM Studio does not take the temperature from the GGUF file and starts every model at 0.8. Set it to 0.2 in the model settings.

Ollama

ollama run hf.co/maylore-ai/Temper-2-Nodel-GGUF:Q8_0

Or locally with the Modelfile from this repository.

ollama create temper-nodel -f Modelfile
ollama run temper-nodel

License

Apache 2.0, same as Qwen3.5-4B. Derivative works, including fine-tunes, merges and quantizations, must keep the attributions in NOTICE (Apache 2.0, section 4(d)).

Downloads last month: 180

GGUF

Model size

4B params

Architecture

qwen35

Hardware compatibility

8-bit

16-bit

Model tree for maylore-ai/Temper-2-Nodel-GGUF

Base model

Qwen/Qwen3.5-4B-Base

Finetuned

Qwen/Qwen3.5-4B

Finetuned

maylore-ai/Temper-2-Nodel

Quantized

(2)

this model