Instructions to use AtomicChat/gemma-4-31B-it-assistant-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use AtomicChat/gemma-4-31B-it-assistant-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="AtomicChat/gemma-4-31B-it-assistant-GGUF", filename="gemma-4-31B-it-assistant.F16.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use AtomicChat/gemma-4-31B-it-assistant-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf AtomicChat/gemma-4-31B-it-assistant-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf AtomicChat/gemma-4-31B-it-assistant-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 AtomicChat/gemma-4-31B-it-assistant-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf AtomicChat/gemma-4-31B-it-assistant-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 AtomicChat/gemma-4-31B-it-assistant-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf AtomicChat/gemma-4-31B-it-assistant-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 AtomicChat/gemma-4-31B-it-assistant-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf AtomicChat/gemma-4-31B-it-assistant-GGUF:Q4_K_M
Use Docker
docker model run hf.co/AtomicChat/gemma-4-31B-it-assistant-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use AtomicChat/gemma-4-31B-it-assistant-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AtomicChat/gemma-4-31B-it-assistant-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AtomicChat/gemma-4-31B-it-assistant-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/AtomicChat/gemma-4-31B-it-assistant-GGUF:Q4_K_M
- Ollama
How to use AtomicChat/gemma-4-31B-it-assistant-GGUF with Ollama:
ollama run hf.co/AtomicChat/gemma-4-31B-it-assistant-GGUF:Q4_K_M
- Unsloth Studio new
How to use AtomicChat/gemma-4-31B-it-assistant-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 AtomicChat/gemma-4-31B-it-assistant-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 AtomicChat/gemma-4-31B-it-assistant-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for AtomicChat/gemma-4-31B-it-assistant-GGUF to start chatting
- Docker Model Runner
How to use AtomicChat/gemma-4-31B-it-assistant-GGUF with Docker Model Runner:
docker model run hf.co/AtomicChat/gemma-4-31B-it-assistant-GGUF:Q4_K_M
- Lemonade
How to use AtomicChat/gemma-4-31B-it-assistant-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull AtomicChat/gemma-4-31B-it-assistant-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.gemma-4-31B-it-assistant-GGUF-Q4_K_M
List all available models
lemonade list
respectfully: expanded CI suite breaks all repo github builds
Posting here as no options to post issues or comments on your repo
Im really appreciative of your hard work getting this version of turboquant with speculative decoding up and running -
i use it every day.
The repo currently is partly broken in that the new expanded CI suite you have recently implemented, causing all builds to fail (these were preexisting warnings) effecting all new pull requests
I appreciate this will eventually improve the quality of the code, but there is no progress this week in fixing the tighter build errors - do you intend to maintain this repo or us ut not a priority for your organisation?