summarizer

Fine-tuned Gemma-3-270M for task summarization and branch naming

Model Details

• Base Model: google/gemma-3-270m-it
• Format: GGUF (quantized for efficient inference)
• Quantization: Q4_K_M
• Use Case: Generating concise task titles and git branch names

Training

• Training Run: https://wandb.ai/vanpelt/summarizer/runs/0t4lcgpb

Usage

With Ollama

ollama pull hf.co/vanpelt/summarizer
ollama run hf.co/vanpelt/summarizer

With llama.cpp

# Download the GGUF file
huggingface-cli download vanpelt/summarizer gemma3-270m-summarizer-Q4_K_M.gguf

# Run with llama.cpp
./main -m gemma3-270m-summarizer-Q4_K_M.gguf -p 'Your prompt here'

Files

• tokenizer.json (31.8 MB)
• tokenizer_config.json (1.1 MB)
• added_tokens.json (0.0 MB)
• chat_template.jinja (0.0 MB)
• Modelfile (0.0 MB)
• template (0.0 MB)
• system (0.0 MB)
• model.safetensors (511.4 MB)
• gemma3-270m-summarizer-Q4_K_M.gguf (241.4 MB)
• special_tokens_map.json (0.0 MB)
• config.json (0.0 MB)
• params (0.0 MB)
• tokenizer.model (4.5 MB)