Instructions to use mradermacher/gemma-4-31B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mradermacher/gemma-4-31B-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("mradermacher/gemma-4-31B-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use mradermacher/gemma-4-31B-GGUF 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 mradermacher/gemma-4-31B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mradermacher/gemma-4-31B-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf mradermacher/gemma-4-31B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mradermacher/gemma-4-31B-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 mradermacher/gemma-4-31B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf mradermacher/gemma-4-31B-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 mradermacher/gemma-4-31B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf mradermacher/gemma-4-31B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/mradermacher/gemma-4-31B-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use mradermacher/gemma-4-31B-GGUF with Ollama:
```
ollama run hf.co/mradermacher/gemma-4-31B-GGUF:Q4_K_M
```

Unsloth Studio

How to use mradermacher/gemma-4-31B-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 mradermacher/gemma-4-31B-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 mradermacher/gemma-4-31B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for mradermacher/gemma-4-31B-GGUF to start chatting

Docker Model Runner
How to use mradermacher/gemma-4-31B-GGUF with Docker Model Runner:
```
docker model run hf.co/mradermacher/gemma-4-31B-GGUF:Q4_K_M
```

Lemonade

How to use mradermacher/gemma-4-31B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull mradermacher/gemma-4-31B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.gemma-4-31B-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

Re-uploads needed?

by bharatcoder - opened Apr 14

Discussion

bharatcoder

Apr 14

Based on the updates, patches and fixes to llama.cpp after the initial launch, do we need a re-upload of these quants?

nicoboss

Apr 14

No most if not all the fixes will get retroactively applied to existing quants as they mainly affect how llama.cpp runs inference on Gemma 4 models. As far I'm aware no serious issues were found with the model itself. Models done very early after release lacked vision but for those, we are requeing for mmproj extraction. Was there any major bugfix that requires quants to be redone that we missed?

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