Instructions to use NobodyWho/Google_Gemma3-4B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use NobodyWho/Google_Gemma3-4B-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="NobodyWho/Google_Gemma3-4B-GGUF", filename="gemma-3-4b-it-Q4_K_M.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use NobodyWho/Google_Gemma3-4B-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_Gemma3-4B-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf NobodyWho/Google_Gemma3-4B-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_Gemma3-4B-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf NobodyWho/Google_Gemma3-4B-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_Gemma3-4B-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf NobodyWho/Google_Gemma3-4B-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_Gemma3-4B-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf NobodyWho/Google_Gemma3-4B-GGUF:Q4_K_M
Use Docker
docker model run hf.co/NobodyWho/Google_Gemma3-4B-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use NobodyWho/Google_Gemma3-4B-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "NobodyWho/Google_Gemma3-4B-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_Gemma3-4B-GGUF", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/NobodyWho/Google_Gemma3-4B-GGUF:Q4_K_M
- Ollama
How to use NobodyWho/Google_Gemma3-4B-GGUF with Ollama:
ollama run hf.co/NobodyWho/Google_Gemma3-4B-GGUF:Q4_K_M
- Unsloth Studio new
How to use NobodyWho/Google_Gemma3-4B-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_Gemma3-4B-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_Gemma3-4B-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_Gemma3-4B-GGUF to start chatting
- Docker Model Runner
How to use NobodyWho/Google_Gemma3-4B-GGUF with Docker Model Runner:
docker model run hf.co/NobodyWho/Google_Gemma3-4B-GGUF:Q4_K_M
- Lemonade
How to use NobodyWho/Google_Gemma3-4B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull NobodyWho/Google_Gemma3-4B-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Google_Gemma3-4B-GGUF-Q4_K_M
List all available models
lemonade list
Gemma 3 4B
Model Capabilities
- Text generation โ instruction-following chat model
- Vision โ understands and reasons about images
- Multilinguality โ 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_Gemma3-4B-GGUF/resolve/main/gemma-3-4b-it-Q4_K_M.gguf
wget https://huggingface.co/NobodyWho/Google_Gemma3-4B-GGUF/resolve/main/mmproj-BF16.gguf
Run with NobodyWho:
from nobodywho import Chat
chat = Chat("./gemma-3-4b-it-Q4_K_M.gguf")
response = chat.ask("What is the capital of Denmark?").completed()
print(response) # Copenhagen!
Vision
from nobodywho import Model, Chat, Prompt, Image, Text
model = Model(
"./gemma-3-4b-it-Q4_K_M.gguf",
projection_model_path="./mmproj-BF16.gguf"
)
chat = Chat(model, system_prompt="You are a helpful assistant.")
prompt = Prompt([
Text("What do you see in this image?"),
Image("./photo.png"),
])
response = chat.ask(prompt).completed()
print(response)
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 | 4B |
| Context length | 131,072 tokens |
| Knowledge cutoff | August 2024 |
| Languages | 140+ |
| License | Gemma Terms of Use |
| Base model | google/gemma-3-4b-it |
Credits
GGUF quantizations provided by unsloth. Thanks!
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