Instructions to use Atharv65/gemma_3_4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
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") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Atharv65/gemma_3_4b 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 Atharv65/gemma_3_4b # Run inference directly in the terminal: llama cli -hf Atharv65/gemma_3_4b
Install from WinGet (Windows)
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
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 Atharv65/gemma_3_4b # Run inference directly in the terminal: ./llama-cli -hf Atharv65/gemma_3_4b
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 Atharv65/gemma_3_4b # Run inference directly in the terminal: ./build/bin/llama-cli -hf Atharv65/gemma_3_4b
Use Docker
docker model run hf.co/Atharv65/gemma_3_4b
- LM Studio
- Jan
- Ollama
How to use Atharv65/gemma_3_4b with Ollama:
ollama run hf.co/Atharv65/gemma_3_4b
- Unsloth Desktop
- Docker Model Runner
How to use Atharv65/gemma_3_4b with Docker Model Runner:
docker model run hf.co/Atharv65/gemma_3_4b
- Lemonade
How to use Atharv65/gemma_3_4b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Atharv65/gemma_3_4b
Run and chat with the model
lemonade run user.gemma_3_4b-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
Download tokenizer.json from Atharv65/gemma_3_4b: direct link, hf CLI and curl.
- Browser
- Download file 33.4 MB
-
https://huggingface.co/Atharv65/gemma_3_4b/resolve/main/tokenizer.json
- Command line
-
hf download hf://Atharv65/gemma_3_4b/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Atharv65/gemma_3_4b/resolve/main/tokenizer.json
33.4 MB
- Xet hash:
- fa66c8c017ade193f7cc37a2b421a1fc461563e803f179a496f7bdda2ec42c21
- Size of remote file:
- 33.4 MB
- SHA256:
- 4667f2089529e8e7657cfb6d1c19910ae71ff5f28aa7ab2ff2763330affad795
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