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--- |
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base_model: microsoft/Phi-4-mini-instruct |
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language: |
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- multilingual |
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- ar |
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- zh |
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- cs |
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- da |
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- nl |
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- en |
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- fi |
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- fr |
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- de |
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- he |
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- hu |
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- it |
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- ja |
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- ko |
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- 'no' |
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- pl |
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- pt |
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- ru |
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- es |
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- sv |
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- th |
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- tr |
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- uk |
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library_name: transformers |
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license: mit |
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license_link: https://huggingface.co/microsoft/Phi-4-mini-instruct/resolve/main/LICENSE |
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pipeline_tag: text-generation |
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tags: |
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- nlp |
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- code |
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- llama-cpp |
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- gguf-my-repo |
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widget: |
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- messages: |
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- role: user |
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content: Can you provide ways to eat combinations of bananas and dragonfruits? |
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--- |
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# Triangle104/Phi-4-mini-instruct-Q5_K_M-GGUF |
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This model was converted to GGUF format from [`microsoft/Phi-4-mini-instruct`](https://huggingface.co/microsoft/Phi-4-mini-instruct) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. |
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Refer to the [original model card](https://huggingface.co/microsoft/Phi-4-mini-instruct) for more details on the model. |
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--- |
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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. |
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--- |
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## Use with llama.cpp |
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Install llama.cpp through brew (works on Mac and Linux) |
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```bash |
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brew install llama.cpp |
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``` |
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Invoke the llama.cpp server or the CLI. |
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### CLI: |
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```bash |
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llama-cli --hf-repo Triangle104/Phi-4-mini-instruct-Q5_K_M-GGUF --hf-file phi-4-mini-instruct-q5_k_m.gguf -p "The meaning to life and the universe is" |
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``` |
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### Server: |
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```bash |
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llama-server --hf-repo Triangle104/Phi-4-mini-instruct-Q5_K_M-GGUF --hf-file phi-4-mini-instruct-q5_k_m.gguf -c 2048 |
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``` |
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Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. |
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Step 1: Clone llama.cpp from GitHub. |
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``` |
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git clone https://github.com/ggerganov/llama.cpp |
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``` |
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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). |
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``` |
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cd llama.cpp && LLAMA_CURL=1 make |
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``` |
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Step 3: Run inference through the main binary. |
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``` |
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./llama-cli --hf-repo Triangle104/Phi-4-mini-instruct-Q5_K_M-GGUF --hf-file phi-4-mini-instruct-q5_k_m.gguf -p "The meaning to life and the universe is" |
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``` |
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or |
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``` |
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./llama-server --hf-repo Triangle104/Phi-4-mini-instruct-Q5_K_M-GGUF --hf-file phi-4-mini-instruct-q5_k_m.gguf -c 2048 |
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``` |
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