Instructions to use QuantFactory/gemma-2-9b-it-SimPO-GGUF-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use QuantFactory/gemma-2-9b-it-SimPO-GGUF-v2 with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="QuantFactory/gemma-2-9b-it-SimPO-GGUF-v2",
	filename="gemma-2-9b-it-SimPO.Q2_K.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use QuantFactory/gemma-2-9b-it-SimPO-GGUF-v2 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 QuantFactory/gemma-2-9b-it-SimPO-GGUF-v2:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf QuantFactory/gemma-2-9b-it-SimPO-GGUF-v2:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf QuantFactory/gemma-2-9b-it-SimPO-GGUF-v2:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf QuantFactory/gemma-2-9b-it-SimPO-GGUF-v2:Q4_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 QuantFactory/gemma-2-9b-it-SimPO-GGUF-v2:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf QuantFactory/gemma-2-9b-it-SimPO-GGUF-v2:Q4_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 QuantFactory/gemma-2-9b-it-SimPO-GGUF-v2:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf QuantFactory/gemma-2-9b-it-SimPO-GGUF-v2:Q4_K_M

Use Docker

docker model run hf.co/QuantFactory/gemma-2-9b-it-SimPO-GGUF-v2:Q4_K_M

LM Studio
Jan
Ollama
How to use QuantFactory/gemma-2-9b-it-SimPO-GGUF-v2 with Ollama:
```
ollama run hf.co/QuantFactory/gemma-2-9b-it-SimPO-GGUF-v2:Q4_K_M
```

Unsloth Studio

How to use QuantFactory/gemma-2-9b-it-SimPO-GGUF-v2 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 QuantFactory/gemma-2-9b-it-SimPO-GGUF-v2 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 QuantFactory/gemma-2-9b-it-SimPO-GGUF-v2 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for QuantFactory/gemma-2-9b-it-SimPO-GGUF-v2 to start chatting

Atomic Chat new
Docker Model Runner
How to use QuantFactory/gemma-2-9b-it-SimPO-GGUF-v2 with Docker Model Runner:
```
docker model run hf.co/QuantFactory/gemma-2-9b-it-SimPO-GGUF-v2:Q4_K_M
```

Lemonade

How to use QuantFactory/gemma-2-9b-it-SimPO-GGUF-v2 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull QuantFactory/gemma-2-9b-it-SimPO-GGUF-v2:Q4_K_M

Run and chat with the model

lemonade run user.gemma-2-9b-it-SimPO-GGUF-v2-Q4_K_M

List all available models

lemonade list

What are the differences between the v2 and the other version of these GGUF files?

by JustData - opened Aug 3, 2024

Discussion

JustData

Aug 3, 2024

You listed two versions for the Gemma 2 9B it SImPO. Both are quantized versions for the same model, but failed to state what the difference is in the model card descriptions. Your "v2" was also updated BEFORE the other presumably v1 version. Can you please update the model card with details for the differences between the two versions?

TouchNight

Aug 27, 2024

Princeton-nlp have update the model 2 times. I guess this v2 is the newer version.

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