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

Libraries

How to use mlabonne/gemma-2b-GGUF with Transformers:

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

llama-cpp-python

How to use mlabonne/gemma-2b-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="mlabonne/gemma-2b-GGUF",
	filename="gemma-2b.Q2_K.gguf",
)

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

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use mlabonne/gemma-2b-GGUF with llama.cpp:

Install from brew

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

Use Docker

docker model run hf.co/mlabonne/gemma-2b-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use mlabonne/gemma-2b-GGUF with Ollama:
```
ollama run hf.co/mlabonne/gemma-2b-GGUF:Q4_K_M
```

Unsloth Studio

How to use mlabonne/gemma-2b-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 mlabonne/gemma-2b-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 mlabonne/gemma-2b-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

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

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

Lemonade

How to use mlabonne/gemma-2b-GGUF with Lemonade:

Pull the model

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

Run and chat with the model

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

List all available models

lemonade list

Unable to run the gemma-2b.Q4_K_M.gguf

by shaikatasif - opened Feb 21, 2024

Discussion

shaikatasif

Feb 21, 2024

hi, First Thank you very much. I was trying to run the gguf version from your quantized version but I encountered with following error. llama_model_load: error loading model: create_tensor: tensor 'output.weight' not found
llama_load_model_from_file: failed to load model
llama_init_from_gpt_params: error: failed to load model 'gemma-2b.Q4_K_M.gguf'
main: error: unable to load model

I think this "general.architecture str = llama " will be gemma instead of llama as in this PR for the gemma model in llama.cpp https://github.com/ggerganov/llama.cpp/pull/5631#issuecomment-1957223298 . Regards

p1ld7a

Feb 21, 2024

Same issue.

Tishin

Feb 21, 2024

•

edited Feb 22, 2024

Same issue: "llama.cpp error: 'create_tensor: tensor 'output.weight' not found'"

I am adding this edit at 9:47pm eastern
I also had this problem with other gemmas from other people. I am using LM Studio. I missed this myself but it clearly states:
"Google DeepMind's Gemma (2B, 7B) is supported in v0.2.15!"
When I'm in the app it says I have v0.2.14 and I have the most current version. No updates available. I am now trying to download a fresh installation of 0.2.15. and then retry.

mwynter

Feb 22, 2024

this doesn't work for me either. I'm also getting that tensor error.

MaziyarPanahi

Feb 22, 2024

None of the GGUF quant models would work because of this issue https://github.com/ggerganov/llama.cpp/issues/5635

I am waiting for this PR to be merged to re-run the quant: https://github.com/ggerganov/llama.cpp/pull/5650

shaikatasif

Feb 22, 2024

Yea, that was my understanding also , I found this one user's quant gguf model seems to be working in my local environment with very bad quality output though. Here is the link for that working quant version gguf. https://huggingface.co/rahuldshetty/gemma-7b-it-gguf-quantized

MaziyarPanahi

Feb 22, 2024

Yea, that was my understanding also , I found this one user's quant gguf model seems to be working in my local environment with very bad quality output though. Here is the link for that working quant version gguf. https://huggingface.co/rahuldshetty/gemma-7b-it-gguf-quantized

Yes, if we use the latest llama.cpp from the main branch it works. It is no longer failing with error, but the quality of the quants is terrible! I am really hoping that PR fixes the issue

mlabonne

Owner Feb 22, 2024

I worked on it today and the quants can be executed with llama.cpp now. Will re-upload everything in a few hours, should be working now.

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