Instructions to use wamo2351/gemma-2-2b-jpn-it-Q3_K_M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use wamo2351/gemma-2-2b-jpn-it-Q3_K_M 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 wamo2351/gemma-2-2b-jpn-it-Q3_K_M:Q3_K_M
# Run inference directly in the terminal:
llama cli -hf wamo2351/gemma-2-2b-jpn-it-Q3_K_M:Q3_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf wamo2351/gemma-2-2b-jpn-it-Q3_K_M:Q3_K_M
# Run inference directly in the terminal:
llama cli -hf wamo2351/gemma-2-2b-jpn-it-Q3_K_M:Q3_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 wamo2351/gemma-2-2b-jpn-it-Q3_K_M:Q3_K_M
# Run inference directly in the terminal:
./llama-cli -hf wamo2351/gemma-2-2b-jpn-it-Q3_K_M:Q3_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 wamo2351/gemma-2-2b-jpn-it-Q3_K_M:Q3_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf wamo2351/gemma-2-2b-jpn-it-Q3_K_M:Q3_K_M

Use Docker

docker model run hf.co/wamo2351/gemma-2-2b-jpn-it-Q3_K_M:Q3_K_M

LM Studio
Jan
Ollama
How to use wamo2351/gemma-2-2b-jpn-it-Q3_K_M with Ollama:
```
ollama run hf.co/wamo2351/gemma-2-2b-jpn-it-Q3_K_M:Q3_K_M
```

Unsloth Studio

How to use wamo2351/gemma-2-2b-jpn-it-Q3_K_M 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 wamo2351/gemma-2-2b-jpn-it-Q3_K_M 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 wamo2351/gemma-2-2b-jpn-it-Q3_K_M to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for wamo2351/gemma-2-2b-jpn-it-Q3_K_M to start chatting

Docker Model Runner
How to use wamo2351/gemma-2-2b-jpn-it-Q3_K_M with Docker Model Runner:
```
docker model run hf.co/wamo2351/gemma-2-2b-jpn-it-Q3_K_M:Q3_K_M
```

Lemonade

How to use wamo2351/gemma-2-2b-jpn-it-Q3_K_M with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull wamo2351/gemma-2-2b-jpn-it-Q3_K_M:Q3_K_M

Run and chat with the model

lemonade run user.gemma-2-2b-jpn-it-Q3_K_M-Q3_K_M

List all available models

lemonade list

Atomic Chat

Gemma 2 2B JPN IT (GGUF / Q3_K_M)

This repository contains the GGUF quantized version of the google/gemma-2-2b-jpn-it model.

このリポジトリは google/gemma-2-2b-jpn-it をGGUF形式（Q3_K_M）に量子化したモデルを含みます。

Model Details / モデル詳細

Base Model: google/gemma-2-2b-jpn-it
Quantization Method: Q3_K_M (3-bit quantization)
Format: GGUF
Quantized by: llama.cpp

License / ライセンス

This model is based on Gemma 2 by Google and is subject to the Gemma Terms of Use. For more details, please refer to the original model card and license.

本モデルはGoogleのGemma 2に基づいており、Gemma 利用規約 (Gemma Terms of Use) に従います。詳細は元モデルのモデルカードおよびライセンスをご確認ください。

Disclaimer / 免責事項

The uploader is not responsible for any damages caused by the use of this model. This model is provided "as is" without warranty of any kind.

このモデルの使用によって生じたいかなる損害についても、アップロード者は責任を負いません。

Downloads last month: 5

GGUF

Model size

3B params

Architecture

gemma2

Hardware compatibility

3-bit

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