Instructions to use MISHANM/google-gemma-2-9b-it.gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use MISHANM/google-gemma-2-9b-it.gguf with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("MISHANM/google-gemma-2-9b-it.gguf", dtype="auto")

llama-cpp-python

How to use MISHANM/google-gemma-2-9b-it.gguf with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="MISHANM/google-gemma-2-9b-it.gguf",
	filename="google--gemma-2-9b-it.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 MISHANM/google-gemma-2-9b-it.gguf with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf MISHANM/google-gemma-2-9b-it.gguf
# Run inference directly in the terminal:
llama-cli -hf MISHANM/google-gemma-2-9b-it.gguf

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf MISHANM/google-gemma-2-9b-it.gguf
# Run inference directly in the terminal:
llama-cli -hf MISHANM/google-gemma-2-9b-it.gguf

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 MISHANM/google-gemma-2-9b-it.gguf
# Run inference directly in the terminal:
./llama-cli -hf MISHANM/google-gemma-2-9b-it.gguf

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 MISHANM/google-gemma-2-9b-it.gguf
# Run inference directly in the terminal:
./build/bin/llama-cli -hf MISHANM/google-gemma-2-9b-it.gguf

Use Docker

docker model run hf.co/MISHANM/google-gemma-2-9b-it.gguf

LM Studio
Jan
Ollama
How to use MISHANM/google-gemma-2-9b-it.gguf with Ollama:
```
ollama run hf.co/MISHANM/google-gemma-2-9b-it.gguf
```

Unsloth Studio new

How to use MISHANM/google-gemma-2-9b-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 MISHANM/google-gemma-2-9b-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 MISHANM/google-gemma-2-9b-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 MISHANM/google-gemma-2-9b-it.gguf to start chatting

Docker Model Runner
How to use MISHANM/google-gemma-2-9b-it.gguf with Docker Model Runner:
```
docker model run hf.co/MISHANM/google-gemma-2-9b-it.gguf
```

Lemonade

How to use MISHANM/google-gemma-2-9b-it.gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull MISHANM/google-gemma-2-9b-it.gguf

Run and chat with the model

lemonade run user.google-gemma-2-9b-it.gguf-{{QUANT_TAG}}

List all available models

lemonade list

MISHANM/google-gemma-2-9b-it.gguf

This model is a GGUF version of the Google gemma-2-9b-it model, optimized for use with the llama.cpp framework. It is designed to run efficiently on CPUs and can be used for various natural language processing tasks.

Model Details

Language: English
Tasks: Text generation
Base Model: google/gemma-2-9b-it

Building and Running the Model

To build and run the model using llama.cpp, follow these steps:

Build llama.cpp Locally

git clone https://github.com/ggerganov/llama.cpp  
cd llama.cpp  
cmake -B build  
cmake --build build --config Release

Run the Model

Navigate to the build directory and run the model with a prompt:

cd llama.cpp/build/bin

Inference with llama.cpp

./llama-cli -m /path/to/model/ -p "Your prompt here" -n 128

Citation Information

@misc{MISHANM/google-gemma-2-9b-it.gguf,
  author = {Mishan Maurya},
  title = {Introducing Google gemma-2-9b-it GGUF Model},
  year = {2025},
  publisher = {Hugging Face},
  journal = {Hugging Face repository},
  
}

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GGUF

Model size

9B params

Architecture

gemma2

Hardware compatibility

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