How to use from
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 MCZK/EZO-gemma-2-2b-jpn-it-GGUF:
# Run inference directly in the terminal:
llama cli -hf MCZK/EZO-gemma-2-2b-jpn-it-GGUF:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf MCZK/EZO-gemma-2-2b-jpn-it-GGUF:
# Run inference directly in the terminal:
llama cli -hf MCZK/EZO-gemma-2-2b-jpn-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 MCZK/EZO-gemma-2-2b-jpn-it-GGUF:
# Run inference directly in the terminal:
./llama-cli -hf MCZK/EZO-gemma-2-2b-jpn-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 MCZK/EZO-gemma-2-2b-jpn-it-GGUF:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf MCZK/EZO-gemma-2-2b-jpn-it-GGUF:
Use Docker
docker model run hf.co/MCZK/EZO-gemma-2-2b-jpn-it-GGUF:
Quick Links

AXCXEPTๆง˜ใฎ AXCXEPT/EZO-gemma-2-2b-jpn-it ใ‚’GGUFๅฝขๅผใซๅค‰ๆ›ใ—ใŸใ‚‚ใฎใงใ™ใ€‚ K้‡ๅญๅŒ–ใƒขใƒ‡ใƒซใซใคใ„ใฆใ‚‚iMatrix้ฉ็”จใ—ใฆใ‚ใ‚Šใพใ™ใ€‚

iMatrixใƒ†ใ‚ญใ‚นใƒˆใฏTFMCๆง˜ใฎc4_en_ja_imatrix.txtใ‚’ไฝฟ็”จใ—ใฆใ„ใพใ™ใ€‚

Downloads last month
466
GGUF
Model size
3B params
Architecture
gemma2
Hardware compatibility
Log In to add your hardware

3-bit

4-bit

5-bit

6-bit

8-bit

16-bit

Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐Ÿ™‹ Ask for provider support

Model tree for MCZK/EZO-gemma-2-2b-jpn-it-GGUF

Quantized
(4)
this model