Instructions to use carcruz97/gemma3_weights with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use carcruz97/gemma3_weights with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="carcruz97/gemma3_weights", filename="gemma-3-270m.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use carcruz97/gemma3_weights 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 carcruz97/gemma3_weights # Run inference directly in the terminal: llama cli -hf carcruz97/gemma3_weights
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf carcruz97/gemma3_weights # Run inference directly in the terminal: llama cli -hf carcruz97/gemma3_weights
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 carcruz97/gemma3_weights # Run inference directly in the terminal: ./llama-cli -hf carcruz97/gemma3_weights
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 carcruz97/gemma3_weights # Run inference directly in the terminal: ./build/bin/llama-cli -hf carcruz97/gemma3_weights
Use Docker
docker model run hf.co/carcruz97/gemma3_weights
- LM Studio
- Jan
- Ollama
How to use carcruz97/gemma3_weights with Ollama:
ollama run hf.co/carcruz97/gemma3_weights
- Unsloth Studio
How to use carcruz97/gemma3_weights 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 carcruz97/gemma3_weights 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 carcruz97/gemma3_weights to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for carcruz97/gemma3_weights to start chatting
- Atomic Chat new
- Docker Model Runner
How to use carcruz97/gemma3_weights with Docker Model Runner:
docker model run hf.co/carcruz97/gemma3_weights
- Lemonade
How to use carcruz97/gemma3_weights with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull carcruz97/gemma3_weights
Run and chat with the model
lemonade run user.gemma3_weights-{{QUANT_TAG}}List all available models
lemonade list
| {"model_format":"gguf","model_family":"gemma3","model_families":["gemma3"],"model_type":"268.10M","file_type":"Q8_0","architecture":"amd64","os":"linux","rootfs":{"type":"layers","diff_ids":["sha256:735af2139dc652bf01112746474883d79a52fa1c19038265d363e3d42556f7a2","sha256:4b19ac7dd2fb1ab2f2818b73454c5a9128ca39875a8fcf686a6b1c36100a0d68","sha256:3e2c24001f9ef57bf7ec959a3658fbb49cdad113cdf394c264da9d16f9bdd132","sha256:339e884a40f6708bc761d367f0c08e448d5bb6f16b3961c340e44e0e4835a004"]}} | |