Instructions to use google/codegemma-2b-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use google/codegemma-2b-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="google/codegemma-2b-GGUF", filename="codegemma-2b-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 google/codegemma-2b-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf google/codegemma-2b-GGUF:F16 # Run inference directly in the terminal: llama-cli -hf google/codegemma-2b-GGUF:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf google/codegemma-2b-GGUF:F16 # Run inference directly in the terminal: llama-cli -hf google/codegemma-2b-GGUF:F16
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 google/codegemma-2b-GGUF:F16 # Run inference directly in the terminal: ./llama-cli -hf google/codegemma-2b-GGUF:F16
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 google/codegemma-2b-GGUF:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf google/codegemma-2b-GGUF:F16
Use Docker
docker model run hf.co/google/codegemma-2b-GGUF:F16
- LM Studio
- Jan
- vLLM
How to use google/codegemma-2b-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "google/codegemma-2b-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "google/codegemma-2b-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/google/codegemma-2b-GGUF:F16
- Ollama
How to use google/codegemma-2b-GGUF with Ollama:
ollama run hf.co/google/codegemma-2b-GGUF:F16
- Unsloth Studio new
How to use google/codegemma-2b-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 google/codegemma-2b-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 google/codegemma-2b-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for google/codegemma-2b-GGUF to start chatting
- Docker Model Runner
How to use google/codegemma-2b-GGUF with Docker Model Runner:
docker model run hf.co/google/codegemma-2b-GGUF:F16
- Lemonade
How to use google/codegemma-2b-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull google/codegemma-2b-GGUF:F16
Run and chat with the model
lemonade run user.codegemma-2b-GGUF-F16
List all available models
lemonade list
How did you convert to gguf?
Hello,
When I have converted to GGUF, I am getting garbage responses.
I have been using llamacpp's GGUF conversion tools.
/root/llamacpp/convert-hf-to-gguf.py hfmodel --outfile model.gguf"
/root/llamacpp/quantize model.gguf model_q4_k_m.gguf Q4_K_M"
/app/gguf-py/scripts/gguf-new-metadata.py model_q4_k_m.gguf model_q4_k_m_with_meta.gguf --special-token prefix '<|fim_prefix|>' --special-token middle '<|fim_middle|>' --special-token suffix '<|fim_suffix|>'
But when I run inferencing on the model, I get garbage responses (random words etc).
Hi @scott0x
Alternatively you can try out this tool: https://huggingface.co/spaces/ggml-org/gguf-my-repo to GGUF any repo out of the box
Hi @scott0x , Sorry for late response, It looks like you are still facing the same issue with garbage responses after using llamacpp's GGUF conversion tools. Can you please try before quantizing, test the model after the initial GGUF conversion but without applying quantization (Q4_K_M) by using below command.
Kindly try and let me know if you have any concerns. Thank you.
