Instructions to use ggml-org/gemma-3n-E4B-it-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use ggml-org/gemma-3n-E4B-it-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="ggml-org/gemma-3n-E4B-it-GGUF", filename="gemma-3n-E4B-it-Q8_0.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use ggml-org/gemma-3n-E4B-it-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 ggml-org/gemma-3n-E4B-it-GGUF:Q8_0 # Run inference directly in the terminal: llama cli -hf ggml-org/gemma-3n-E4B-it-GGUF:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf ggml-org/gemma-3n-E4B-it-GGUF:Q8_0 # Run inference directly in the terminal: llama cli -hf ggml-org/gemma-3n-E4B-it-GGUF:Q8_0
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 ggml-org/gemma-3n-E4B-it-GGUF:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf ggml-org/gemma-3n-E4B-it-GGUF:Q8_0
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 ggml-org/gemma-3n-E4B-it-GGUF:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf ggml-org/gemma-3n-E4B-it-GGUF:Q8_0
Use Docker
docker model run hf.co/ggml-org/gemma-3n-E4B-it-GGUF:Q8_0
- LM Studio
- Jan
- Ollama
How to use ggml-org/gemma-3n-E4B-it-GGUF with Ollama:
ollama run hf.co/ggml-org/gemma-3n-E4B-it-GGUF:Q8_0
- Unsloth Studio
How to use ggml-org/gemma-3n-E4B-it-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 ggml-org/gemma-3n-E4B-it-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 ggml-org/gemma-3n-E4B-it-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for ggml-org/gemma-3n-E4B-it-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use ggml-org/gemma-3n-E4B-it-GGUF with Docker Model Runner:
docker model run hf.co/ggml-org/gemma-3n-E4B-it-GGUF:Q8_0
- Lemonade
How to use ggml-org/gemma-3n-E4B-it-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ggml-org/gemma-3n-E4B-it-GGUF:Q8_0
Run and chat with the model
lemonade run user.gemma-3n-E4B-it-GGUF-Q8_0
List all available models
lemonade list
Create README.md
Browse files
README.md
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---
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license: gemma
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library_name: gguf
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base_model: google/gemma-3n-e4b-it
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---
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> [!Note]
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> This version does not contain multimodal support. We are still working on adding multimodal.
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# Gemma 3n model card
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**Original model**: https://huggingface.co/google/gemma-3n-E4B-it
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**Model Page**: [Gemma 3n](https://ai.google.dev/gemma/docs/gemma-3n)
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**Resources and Technical Documentation**:
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- [Responsible Generative AI Toolkit](https://ai.google.dev/responsible)
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- [Gemma on Kaggle](https://www.kaggle.com/models/google/gemma-3n)
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- [Gemma on HuggingFace](https://huggingface.co/collections/google/gemma-3n-685065323f5984ef315c93f4)
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- [Gemma on Vertex Model Garden](https://console.cloud.google.com/vertex-ai/publishers/google/model-garden/gemma3n)
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**Terms of Use**: [Terms](https://ai.google.dev/gemma/terms)\
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**Authors**: Google DeepMind
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## Example usage
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### With llama.cpp
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To install llama.cpp on your system, see [installation guide](https://github.com/ggml-org/llama.cpp/blob/master/README.md)
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```sh
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llama-cli -m ggml-org/gemma-3n-E4B-it-GGUF
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```
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### With ollama
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```sh
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ollama run ggml-org/gemma-3n-E4B-it-GGUF
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```
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### With LM Studio
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Search for `gemma-3n-E4B-it-GGUF` and add it to your model library
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