Instructions to use MatclassAI/Matclass-Gemma-2b-v1-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use MatclassAI/Matclass-Gemma-2b-v1-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="MatclassAI/Matclass-Gemma-2b-v1-GGUF", filename="gemma-2-2b-it.Q4_K_M.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use MatclassAI/Matclass-Gemma-2b-v1-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf MatclassAI/Matclass-Gemma-2b-v1-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf MatclassAI/Matclass-Gemma-2b-v1-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 MatclassAI/Matclass-Gemma-2b-v1-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf MatclassAI/Matclass-Gemma-2b-v1-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 MatclassAI/Matclass-Gemma-2b-v1-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf MatclassAI/Matclass-Gemma-2b-v1-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 MatclassAI/Matclass-Gemma-2b-v1-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf MatclassAI/Matclass-Gemma-2b-v1-GGUF:Q4_K_M
Use Docker
docker model run hf.co/MatclassAI/Matclass-Gemma-2b-v1-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use MatclassAI/Matclass-Gemma-2b-v1-GGUF with Ollama:
ollama run hf.co/MatclassAI/Matclass-Gemma-2b-v1-GGUF:Q4_K_M
- Unsloth Studio new
How to use MatclassAI/Matclass-Gemma-2b-v1-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 MatclassAI/Matclass-Gemma-2b-v1-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 MatclassAI/Matclass-Gemma-2b-v1-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for MatclassAI/Matclass-Gemma-2b-v1-GGUF to start chatting
- Docker Model Runner
How to use MatclassAI/Matclass-Gemma-2b-v1-GGUF with Docker Model Runner:
docker model run hf.co/MatclassAI/Matclass-Gemma-2b-v1-GGUF:Q4_K_M
- Lemonade
How to use MatclassAI/Matclass-Gemma-2b-v1-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull MatclassAI/Matclass-Gemma-2b-v1-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Matclass-Gemma-2b-v1-GGUF-Q4_K_M
List all available models
lemonade list
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf MatclassAI/Matclass-Gemma-2b-v1-GGUF:Q4_K_M# Run inference directly in the terminal:
llama-cli -hf MatclassAI/Matclass-Gemma-2b-v1-GGUF:Q4_K_MUse 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 MatclassAI/Matclass-Gemma-2b-v1-GGUF:Q4_K_M# Run inference directly in the terminal:
./llama-cli -hf MatclassAI/Matclass-Gemma-2b-v1-GGUF:Q4_K_MBuild 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 MatclassAI/Matclass-Gemma-2b-v1-GGUF:Q4_K_M# Run inference directly in the terminal:
./build/bin/llama-cli -hf MatclassAI/Matclass-Gemma-2b-v1-GGUF:Q4_K_MUse Docker
docker model run hf.co/MatclassAI/Matclass-Gemma-2b-v1-GGUF:Q4_K_MMatclass-Gemma-2b-v1-GGUF : GGUF
What Matclass is? Matclass is better ai than its base model in multiple things, better at chatting, it never lies about its knowledge unlike other ai's that always tells you that they know everything Matclass can help you with creating cheats, just be carefull with anithcheats and rules, make sure you are playing on local server or with -insecure if game uses VAC anticheat, its not good when you make other people sad
We will make more models soon!
This model was finetuned and converted to GGUF format using Unsloth.
Example usage:
- For text only LLMs:
llama-cli -hf MatclassAI/Matclass-Gemma-2b-v1-GGUF --jinja - For multimodal models:
llama-mtmd-cli -hf MatclassAI/Matclass-Gemma-2b-v1-GGUF --jinja
Available Model files:
gemma-2-2b-it.Q4_K_M.gguf
Ollama
An Ollama Modelfile is included for easy deployment.
Note
The model's BOS token behavior was adjusted for GGUF compatibility.
This was trained 2x faster with Unsloth

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Base model
google/gemma-2b-it
Install from brew
# Start a local OpenAI-compatible server with a web UI: llama-server -hf MatclassAI/Matclass-Gemma-2b-v1-GGUF:Q4_K_M# Run inference directly in the terminal: llama-cli -hf MatclassAI/Matclass-Gemma-2b-v1-GGUF:Q4_K_M