Instructions to use NobodyWho/Google_Gemma3-270M-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use NobodyWho/Google_Gemma3-270M-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="NobodyWho/Google_Gemma3-270M-GGUF",
	filename="gemma-3-270m-it-Q4_K_M.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use NobodyWho/Google_Gemma3-270M-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf NobodyWho/Google_Gemma3-270M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf NobodyWho/Google_Gemma3-270M-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf NobodyWho/Google_Gemma3-270M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf NobodyWho/Google_Gemma3-270M-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 NobodyWho/Google_Gemma3-270M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf NobodyWho/Google_Gemma3-270M-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 NobodyWho/Google_Gemma3-270M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf NobodyWho/Google_Gemma3-270M-GGUF:Q4_K_M

Use Docker

docker model run hf.co/NobodyWho/Google_Gemma3-270M-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use NobodyWho/Google_Gemma3-270M-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "NobodyWho/Google_Gemma3-270M-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": "NobodyWho/Google_Gemma3-270M-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/NobodyWho/Google_Gemma3-270M-GGUF:Q4_K_M

Ollama
How to use NobodyWho/Google_Gemma3-270M-GGUF with Ollama:
```
ollama run hf.co/NobodyWho/Google_Gemma3-270M-GGUF:Q4_K_M
```

Unsloth Studio new

How to use NobodyWho/Google_Gemma3-270M-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 NobodyWho/Google_Gemma3-270M-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 NobodyWho/Google_Gemma3-270M-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for NobodyWho/Google_Gemma3-270M-GGUF to start chatting

Docker Model Runner
How to use NobodyWho/Google_Gemma3-270M-GGUF with Docker Model Runner:
```
docker model run hf.co/NobodyWho/Google_Gemma3-270M-GGUF:Q4_K_M
```

Lemonade

How to use NobodyWho/Google_Gemma3-270M-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull NobodyWho/Google_Gemma3-270M-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Google_Gemma3-270M-GGUF-Q4_K_M

List all available models

lemonade list

Gemma 3 270M

Model Capabilities

Text generation — instruction-following chat model
Multilinguality — supports over 140 languages

The full description can be found at the original model page.

Getting Started

Download the model locally through the huggingface UI or run this in the command line:

wget https://huggingface.co/NobodyWho/Google_Gemma3-270M-GGUF/resolve/main/gemma-3-270m-it-Q4_K_M.gguf

Run with NobodyWho:

from nobodywho import Chat

chat = Chat("./gemma-3-270m-it-Q4_K_M.gguf")
response = chat.ask("What is the capital of Denmark?").completed()
print(response) # Copenhagen!

Benchmarks

Coming soon.

How are these GGUFs different?

These GGUF files serve mainly for NobodyWho inference library and are a way that we can guarantee that they will include all of the necessary info to be truly portable (sampler config, token descriptions, etc.). It is our informal effort to somehow arrive at more standardized GGUF files, which contain everything the runtime needs so that the user can have effortless experience using them, without additional fiddling or patching stuff up for every single model.

Model Details

Property	Value
Parameters	270M
Context length	32,768 tokens
Knowledge cutoff	August 2024
Languages	140+
License	Gemma Terms of Use
Base model	google/gemma-3-270m-it

Credits

GGUF quantizations provided by unsloth. Thanks!

Downloads last month: 334

GGUF

Model size

0.3B params

Architecture

gemma3

Hardware compatibility

4-bit

Model tree for NobodyWho/Google_Gemma3-270M-GGUF

Base model

google/gemma-3-270m

Finetuned

google/gemma-3-270m-it

Quantized

(89)

this model

Collection including NobodyWho/Google_Gemma3-270M-GGUF

Gemma 3

Collection

4 items • Updated about 1 month ago