Instructions to use fivetech/gemma-1.1-7b-it-Q2_K-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use fivetech/gemma-1.1-7b-it-Q2_K-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("fivetech/gemma-1.1-7b-it-Q2_K-GGUF", dtype="auto")

llama-cpp-python

How to use fivetech/gemma-1.1-7b-it-Q2_K-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="fivetech/gemma-1.1-7b-it-Q2_K-GGUF",
	filename="gemma-1.1-7b-it.Q2_K.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 fivetech/gemma-1.1-7b-it-Q2_K-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf fivetech/gemma-1.1-7b-it-Q2_K-GGUF:Q2_K
# Run inference directly in the terminal:
llama-cli -hf fivetech/gemma-1.1-7b-it-Q2_K-GGUF:Q2_K

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf fivetech/gemma-1.1-7b-it-Q2_K-GGUF:Q2_K
# Run inference directly in the terminal:
llama-cli -hf fivetech/gemma-1.1-7b-it-Q2_K-GGUF:Q2_K

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 fivetech/gemma-1.1-7b-it-Q2_K-GGUF:Q2_K
# Run inference directly in the terminal:
./llama-cli -hf fivetech/gemma-1.1-7b-it-Q2_K-GGUF:Q2_K

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 fivetech/gemma-1.1-7b-it-Q2_K-GGUF:Q2_K
# Run inference directly in the terminal:
./build/bin/llama-cli -hf fivetech/gemma-1.1-7b-it-Q2_K-GGUF:Q2_K

Use Docker

docker model run hf.co/fivetech/gemma-1.1-7b-it-Q2_K-GGUF:Q2_K

LM Studio
Jan
Ollama
How to use fivetech/gemma-1.1-7b-it-Q2_K-GGUF with Ollama:
```
ollama run hf.co/fivetech/gemma-1.1-7b-it-Q2_K-GGUF:Q2_K
```

Unsloth Studio

How to use fivetech/gemma-1.1-7b-it-Q2_K-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 fivetech/gemma-1.1-7b-it-Q2_K-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 fivetech/gemma-1.1-7b-it-Q2_K-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for fivetech/gemma-1.1-7b-it-Q2_K-GGUF to start chatting

Docker Model Runner
How to use fivetech/gemma-1.1-7b-it-Q2_K-GGUF with Docker Model Runner:
```
docker model run hf.co/fivetech/gemma-1.1-7b-it-Q2_K-GGUF:Q2_K
```

Lemonade

How to use fivetech/gemma-1.1-7b-it-Q2_K-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull fivetech/gemma-1.1-7b-it-Q2_K-GGUF:Q2_K

Run and chat with the model

lemonade run user.gemma-1.1-7b-it-Q2_K-GGUF-Q2_K

List all available models

lemonade list

fivetech/gemma-1.1-7b-it-Q2_K-GGUF

This model was converted to GGUF format from google/gemma-1.1-7b-it using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

Use with llama.cpp

Install llama.cpp through brew.

brew install ggerganov/ggerganov/llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo fivetech/gemma-1.1-7b-it-Q2_K-GGUF --model gemma-1.1-7b-it.Q2_K.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo fivetech/gemma-1.1-7b-it-Q2_K-GGUF --model gemma-1.1-7b-it.Q2_K.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

git clone https://github.com/ggerganov/llama.cpp &&             cd llama.cpp &&             make &&             ./main -m gemma-1.1-7b-it.Q2_K.gguf -n 128

Downloads last month: 15

GGUF

Model size

9B params

Architecture

gemma

Hardware compatibility

2-bit

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