How to use Atharv65/gemma_3_4b with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Atharv65/gemma_3_4b", device_map="auto")
How to use Atharv65/gemma_3_4b with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf Atharv65/gemma_3_4b # Run inference directly in the terminal: llama cli -hf Atharv65/gemma_3_4b
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Atharv65/gemma_3_4b # Run inference directly in the terminal: llama cli -hf Atharv65/gemma_3_4b
# 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 Atharv65/gemma_3_4b # Run inference directly in the terminal: ./llama-cli -hf Atharv65/gemma_3_4b
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 Atharv65/gemma_3_4b # Run inference directly in the terminal: ./build/bin/llama-cli -hf Atharv65/gemma_3_4b
docker model run hf.co/Atharv65/gemma_3_4b
How to use Atharv65/gemma_3_4b with Ollama:
ollama run hf.co/Atharv65/gemma_3_4b
How to use Atharv65/gemma_3_4b with Docker Model Runner:
How to use Atharv65/gemma_3_4b with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Atharv65/gemma_3_4b
lemonade run user.gemma_3_4b-{{QUANT_TAG}}
lemonade list
