Instructions to use sayhan/gemma-2b-it-GGUF-quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use sayhan/gemma-2b-it-GGUF-quantized 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 sayhan/gemma-2b-it-GGUF-quantized:Q4_K_M # Run inference directly in the terminal: llama cli -hf sayhan/gemma-2b-it-GGUF-quantized:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf sayhan/gemma-2b-it-GGUF-quantized:Q4_K_M # Run inference directly in the terminal: llama cli -hf sayhan/gemma-2b-it-GGUF-quantized: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 sayhan/gemma-2b-it-GGUF-quantized:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf sayhan/gemma-2b-it-GGUF-quantized: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 sayhan/gemma-2b-it-GGUF-quantized:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf sayhan/gemma-2b-it-GGUF-quantized:Q4_K_M
Use Docker
docker model run hf.co/sayhan/gemma-2b-it-GGUF-quantized:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use sayhan/gemma-2b-it-GGUF-quantized with Ollama:
ollama run hf.co/sayhan/gemma-2b-it-GGUF-quantized:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use sayhan/gemma-2b-it-GGUF-quantized with Docker Model Runner:
docker model run hf.co/sayhan/gemma-2b-it-GGUF-quantized:Q4_K_M
- Lemonade
How to use sayhan/gemma-2b-it-GGUF-quantized with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull sayhan/gemma-2b-it-GGUF-quantized:Q4_K_M
Run and chat with the model
lemonade run user.gemma-2b-it-GGUF-quantized-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Difference between K_M and K_M_v2 models
#1
by samikr - opened
Hi,
What is the difference between K_M and K_M_v2 (and similarly for K_S and K_L) models? Any recommendation on which one should be tried out?
Thanks.
Use the ones with the "v2" suffix. The other ones weren't properly quantized. I forgot to delete the old files. I apologize for my mistake.
Thanks - I am trying out with a v2 one - assuming that it is better than the other one! :-)
samikr changed discussion status to closed