metadata

base_model: microsoft/Phi-4-mini-instruct
language:
  - multilingual
  - ar
  - zh
  - cs
  - da
  - nl
  - en
  - fi
  - fr
  - de
  - he
  - hu
  - it
  - ja
  - ko
  - 'no'
  - pl
  - pt
  - ru
  - es
  - sv
  - th
  - tr
  - uk
library_name: transformers
license: mit
license_link: https://huggingface.co/microsoft/Phi-4-mini-instruct/resolve/main/LICENSE
pipeline_tag: text-generation
tags:
  - nlp
  - code
  - llama-cpp
  - gguf-my-repo
widget:
  - messages:
      - role: user
        content: Can you provide ways to eat combinations of bananas and dragonfruits?

Triangle104/Phi-4-mini-instruct-Q4_K_S-GGUF

This model was converted to GGUF format from microsoft/Phi-4-mini-instruct using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

Phi-4-mini-instruct is a lightweight open model built upon synthetic data and filtered publicly available websites - with a focus on high-quality, reasoning dense data. The model belongs to the Phi-4 model family and supports 128K token context length. The model underwent an enhancement process, incorporating both supervised fine-tuning and direct preference optimization to support precise instruction adherence and robust safety measures.

Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo Triangle104/Phi-4-mini-instruct-Q4_K_S-GGUF --hf-file phi-4-mini-instruct-q4_k_s.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/Phi-4-mini-instruct-Q4_K_S-GGUF --hf-file phi-4-mini-instruct-q4_k_s.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo Triangle104/Phi-4-mini-instruct-Q4_K_S-GGUF --hf-file phi-4-mini-instruct-q4_k_s.gguf -p "The meaning to life and the universe is"

./llama-server --hf-repo Triangle104/Phi-4-mini-instruct-Q4_K_S-GGUF --hf-file phi-4-mini-instruct-q4_k_s.gguf -c 2048