Instructions to use halilergul1/gemma-2b-it-q4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use halilergul1/gemma-2b-it-q4 with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="halilergul1/gemma-2b-it-q4",
	filename="gemma2b-Q4.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use halilergul1/gemma-2b-it-q4 with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf halilergul1/gemma-2b-it-q4
# Run inference directly in the terminal:
llama-cli -hf halilergul1/gemma-2b-it-q4

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf halilergul1/gemma-2b-it-q4
# Run inference directly in the terminal:
llama-cli -hf halilergul1/gemma-2b-it-q4

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 halilergul1/gemma-2b-it-q4
# Run inference directly in the terminal:
./llama-cli -hf halilergul1/gemma-2b-it-q4

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 halilergul1/gemma-2b-it-q4
# Run inference directly in the terminal:
./build/bin/llama-cli -hf halilergul1/gemma-2b-it-q4

Use Docker

docker model run hf.co/halilergul1/gemma-2b-it-q4

LM Studio
Jan
Ollama
How to use halilergul1/gemma-2b-it-q4 with Ollama:
```
ollama run hf.co/halilergul1/gemma-2b-it-q4
```

Unsloth Studio new

How to use halilergul1/gemma-2b-it-q4 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 halilergul1/gemma-2b-it-q4 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 halilergul1/gemma-2b-it-q4 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for halilergul1/gemma-2b-it-q4 to start chatting

Docker Model Runner
How to use halilergul1/gemma-2b-it-q4 with Docker Model Runner:
```
docker model run hf.co/halilergul1/gemma-2b-it-q4
```

Lemonade

How to use halilergul1/gemma-2b-it-q4 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull halilergul1/gemma-2b-it-q4

Run and chat with the model

lemonade run user.gemma-2b-it-q4-{{QUANT_TAG}}

List all available models

lemonade list

YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

This is a gguf formatted parameters of instruction-tuned of Gemma-2B model, enjoy!

Downloads last month: 5

GGUF

Model size

3B params

Architecture

gemma

Hardware compatibility

We're not able to determine the quantization variants.

View all variants

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support