Instructions to use bartowski/gemma-2-27b-it-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use bartowski/gemma-2-27b-it-GGUF with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="bartowski/gemma-2-27b-it-GGUF")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("bartowski/gemma-2-27b-it-GGUF", dtype="auto")

llama-cpp-python

How to use bartowski/gemma-2-27b-it-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="bartowski/gemma-2-27b-it-GGUF",
	filename="gemma-2-27b-it-IQ2_M.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use bartowski/gemma-2-27b-it-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf bartowski/gemma-2-27b-it-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf bartowski/gemma-2-27b-it-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf bartowski/gemma-2-27b-it-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf bartowski/gemma-2-27b-it-GGUF: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 bartowski/gemma-2-27b-it-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf bartowski/gemma-2-27b-it-GGUF: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 bartowski/gemma-2-27b-it-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf bartowski/gemma-2-27b-it-GGUF:Q4_K_M

Use Docker

docker model run hf.co/bartowski/gemma-2-27b-it-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use bartowski/gemma-2-27b-it-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "bartowski/gemma-2-27b-it-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "bartowski/gemma-2-27b-it-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/bartowski/gemma-2-27b-it-GGUF:Q4_K_M

SGLang

How to use bartowski/gemma-2-27b-it-GGUF with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "bartowski/gemma-2-27b-it-GGUF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "bartowski/gemma-2-27b-it-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "bartowski/gemma-2-27b-it-GGUF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "bartowski/gemma-2-27b-it-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use bartowski/gemma-2-27b-it-GGUF with Ollama:
```
ollama run hf.co/bartowski/gemma-2-27b-it-GGUF:Q4_K_M
```

Unsloth Studio new

How to use bartowski/gemma-2-27b-it-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 bartowski/gemma-2-27b-it-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 bartowski/gemma-2-27b-it-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for bartowski/gemma-2-27b-it-GGUF to start chatting

Docker Model Runner
How to use bartowski/gemma-2-27b-it-GGUF with Docker Model Runner:
```
docker model run hf.co/bartowski/gemma-2-27b-it-GGUF:Q4_K_M
```

Lemonade

How to use bartowski/gemma-2-27b-it-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull bartowski/gemma-2-27b-it-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.gemma-2-27b-it-GGUF-Q4_K_M

List all available models

lemonade list

Interview request: genAI evaluation & documentation

#14

by meggymuggy - opened Sep 4, 2024

Discussion

meggymuggy

Sep 4, 2024

Hi! We are researchers from Carnegie Mellon University conducting a study on the evaluation and documentation practices of generative AI developers. Given the popularity and success of your model, we're particularly interested in learning from your team's experiences.
Our study aims to:

Understand current practices in Gen AI model evaluation and reporting
Identify challenges faced by developers in these areas
Explore potential improvements in evaluation and documentation processes

We're seeking participants with hands-on experience in these aspects of Gen AI development. Would any members of your team be interested in participating in a (compensated) interview to share their insights?
For more details about the study and to express interest, please visit our recruitment page: https://forms.gle/fbn4734YxrRg6mkBA

bartowski

Owner Sep 4, 2024

I didn't actually make this model, this is Google's model that I quantized. You should likely reach out to them for any real information and experiences:

https://huggingface.co/google/gemma-2-27b-it

meggymuggy

Sep 4, 2024

Hi! Thanks for your response! We noticed you have a fair few models on hugging face. If there are any generative models that you feel you did significant development/eval/documentation on, could you direct us to them?

bartowski

Owner Sep 6, 2024

Ah I didn't actually "make" any of these, the original authors upload the full model weights, then I download them, compress them, and re-upload for the general population :)

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