A newer version of this model is available: cngchis/phi4-mini-intent

About

Static GGUF quantization for an Intent Classification model.

This model is converted from a Hugging Face checkpoint and optimized for local inference using llama.cpp compatible runtimes.

The model is designed for predicting intent labels from user input text.


Usage

If you are unsure how to use GGUF files, refer to: https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF

Basic usage with llama.cpp:

./main -m model.Q4_K_M.gguf -p "Your input text here"

For classification tasks, ensure your prompt format matches the training setup (e.g., instruction or label format).


Provided Quant

Link Type Size/GB Notes
GGUF Q4_K_M ~X.X 2.5 recommended balance of speed and quality

Notes

  • This model is fine-tuned for intent classification tasks only
  • Best performance when input follows the same format as training data
  • Q4_K_M provides a good trade-off between accuracy and inference speed

FAQ / Requests

Thanks

Thanks to the open-source GGUF ecosystem (llama.cpp, ggml) and Hugging Face community.

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