Instructions to use S4MPL3BI4S/gemma4-coding-agent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use S4MPL3BI4S/gemma4-coding-agent with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="S4MPL3BI4S/gemma4-coding-agent",
	filename="gemma-4-E4B-it.BF16-mmproj.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use S4MPL3BI4S/gemma4-coding-agent with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf S4MPL3BI4S/gemma4-coding-agent:BF16
# Run inference directly in the terminal:
llama-cli -hf S4MPL3BI4S/gemma4-coding-agent:BF16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf S4MPL3BI4S/gemma4-coding-agent:BF16
# Run inference directly in the terminal:
llama-cli -hf S4MPL3BI4S/gemma4-coding-agent:BF16

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 S4MPL3BI4S/gemma4-coding-agent:BF16
# Run inference directly in the terminal:
./llama-cli -hf S4MPL3BI4S/gemma4-coding-agent:BF16

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 S4MPL3BI4S/gemma4-coding-agent:BF16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf S4MPL3BI4S/gemma4-coding-agent:BF16

Use Docker

docker model run hf.co/S4MPL3BI4S/gemma4-coding-agent:BF16

LM Studio
Jan
Ollama
How to use S4MPL3BI4S/gemma4-coding-agent with Ollama:
```
ollama run hf.co/S4MPL3BI4S/gemma4-coding-agent:BF16
```

Unsloth Studio new

How to use S4MPL3BI4S/gemma4-coding-agent 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 S4MPL3BI4S/gemma4-coding-agent 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 S4MPL3BI4S/gemma4-coding-agent to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for S4MPL3BI4S/gemma4-coding-agent to start chatting

Docker Model Runner
How to use S4MPL3BI4S/gemma4-coding-agent with Docker Model Runner:
```
docker model run hf.co/S4MPL3BI4S/gemma4-coding-agent:BF16
```

Lemonade

How to use S4MPL3BI4S/gemma4-coding-agent with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull S4MPL3BI4S/gemma4-coding-agent:BF16

Run and chat with the model

lemonade run user.gemma4-coding-agent-BF16

List all available models

lemonade list

gemma4-coding-agent / processor_config.json

S4MPL3BI4S

Upload model trained with Unsloth

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	{
	"audio_ms_per_token": 40,
	"audio_seq_length": 750,
	"feature_extractor": {
	"dither": 0.0,
	"feature_extractor_type": "Gemma4AudioFeatureExtractor",
	"feature_size": 128,
	"fft_length": 512,
	"fft_overdrive": false,
	"frame_length": 320,
	"hop_length": 160,
	"input_scale_factor": 1.0,
	"max_frequency": 8000.0,
	"mel_floor": 0.001,
	"min_frequency": 0.0,
	"padding_side": "left",
	"padding_value": 0.0,
	"per_bin_mean": null,
	"per_bin_stddev": null,
	"preemphasis": 0.0,
	"preemphasis_htk_flavor": true,
	"return_attention_mask": true,
	"sampling_rate": 16000
	},
	"image_processor": {
	"do_convert_rgb": true,
	"do_normalize": false,
	"do_rescale": true,
	"do_resize": true,
	"image_mean": [
	0.0,
	0.0,
	0.0
	],
	"image_processor_type": "Gemma4ImageProcessor",
	"image_seq_length": 280,
	"image_std": [
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	1.0,
	1.0
	],
	"max_soft_tokens": 280,
	"patch_size": 16,
	"pooling_kernel_size": 3,
	"resample": 3,
	"rescale_factor": 0.00392156862745098
	},
	"image_seq_length": 280,
	"processor_class": "Gemma4Processor",
	"video_processor": {
	"do_convert_rgb": true,
	"do_normalize": true,
	"do_rescale": true,
	"do_resize": true,
	"do_sample_frames": true,
	"image_mean": [
	0.0,
	0.0,
	0.0
	],
	"image_std": [
	1.0,
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	"max_soft_tokens": 70,
	"num_frames": 32,
	"patch_size": 16,
	"pooling_kernel_size": 3,
	"resample": 3,
	"rescale_factor": 0.00392156862745098,
	"return_metadata": false,
	"video_processor_type": "Gemma4VideoProcessor"
	}
	}