Instructions to use chatpdflocal/gemma-3-12b-it-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use chatpdflocal/gemma-3-12b-it-gguf with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="chatpdflocal/gemma-3-12b-it-gguf", filename="gemma-3-12b-it-q4_0.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 chatpdflocal/gemma-3-12b-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 chatpdflocal/gemma-3-12b-it-gguf:Q4_0 # Run inference directly in the terminal: llama-cli -hf chatpdflocal/gemma-3-12b-it-gguf:Q4_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf chatpdflocal/gemma-3-12b-it-gguf:Q4_0 # Run inference directly in the terminal: llama-cli -hf chatpdflocal/gemma-3-12b-it-gguf:Q4_0
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 chatpdflocal/gemma-3-12b-it-gguf:Q4_0 # Run inference directly in the terminal: ./llama-cli -hf chatpdflocal/gemma-3-12b-it-gguf:Q4_0
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 chatpdflocal/gemma-3-12b-it-gguf:Q4_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf chatpdflocal/gemma-3-12b-it-gguf:Q4_0
Use Docker
docker model run hf.co/chatpdflocal/gemma-3-12b-it-gguf:Q4_0
- LM Studio
- Jan
- Ollama
How to use chatpdflocal/gemma-3-12b-it-gguf with Ollama:
ollama run hf.co/chatpdflocal/gemma-3-12b-it-gguf:Q4_0
- Unsloth Studio new
How to use chatpdflocal/gemma-3-12b-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 chatpdflocal/gemma-3-12b-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 chatpdflocal/gemma-3-12b-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 chatpdflocal/gemma-3-12b-it-gguf to start chatting
- Docker Model Runner
How to use chatpdflocal/gemma-3-12b-it-gguf with Docker Model Runner:
docker model run hf.co/chatpdflocal/gemma-3-12b-it-gguf:Q4_0
- Lemonade
How to use chatpdflocal/gemma-3-12b-it-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull chatpdflocal/gemma-3-12b-it-gguf:Q4_0
Run and chat with the model
lemonade run user.gemma-3-12b-it-gguf-Q4_0
List all available models
lemonade list
It's a gguf model file of gemma-3-12b-it, which is developed by Google.
It's very applicable for deploying and using in PCs, laptops or mobiles.
gemma-3-12b-it-q4_0.gguf is the quantization-aware trained(QAT) checkpoints of Gemma 3, 3x less VRAM, while retaining almost the same quality. Recommend it.
Useful local intelligent documents assistant AI tools:
MyDocs is a desktop App which supports Windows and MacOS, and especially for professionals who demand absolute privacy. 100% local processing ensuring total documents sovereignty and zero-cloud dependency.
If you are using Zotero for managing and reading your personal PDFs, PapersGPT is a free plugin which can assist you to chat PDFs effectively by your local gemma-3-12b-it. you can download ChatPDFLocal MacOS app from here, load one or batch PDF files at will, and quickly experience the effect of the model through chat reading.
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