llm.create_chat_completion(
messages = "\"The tower is 324 metres (1,063 ft) tall, about the same height as an 81-storey building, and the tallest structure in Paris. Its base is square, measuring 125 metres (410 ft) on each side. During its construction, the Eiffel Tower surpassed the Washington Monument to become the tallest man-made structure in the world, a title it held for 41 years until the Chrysler Building in New York City was finished in 1930. It was the first structure to reach a height of 300 metres. Due to the addition of a broadcasting aerial at the top of the tower in 1957, it is now taller than the Chrysler Building by 5.2 metres (17 ft). Excluding transmitters, the Eiffel Tower is the second tallest free-standing structure in France after the Millau Viaduct.\""
)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)
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Hardware compatibility
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4-bit
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="vanpelt/summarizer", filename="gemma3-270m-summarizer-Q4_K_M.gguf", )