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--- |
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license: mit |
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license_link: https://huggingface.co./microsoft/phi-4/resolve/main/LICENSE |
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language: |
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- en |
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pipeline_tag: text-generation |
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tags: |
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- phi |
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- nlp |
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- math |
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- code |
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- chat |
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- conversational |
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- llama-cpp |
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- gguf-my-repo |
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inference: |
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parameters: |
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temperature: 0 |
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widget: |
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- messages: |
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- role: user |
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content: How should I explain the Internet? |
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library_name: transformers |
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base_model: microsoft/phi-4 |
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--- |
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# Triangle104/phi-4-Q8_0-GGUF |
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This model was converted to GGUF format from [`microsoft/phi-4`](https://huggingface.co./microsoft/phi-4) 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) for more details on the model. |
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--- |
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Model details: |
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- |
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Developers |
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- |
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Microsoft Research |
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Description |
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- |
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phi-4 is a state-of-the-art open model built upon a blend of synthetic datasets, data from filtered public domain websites, and acquired academic books and Q&A datasets. The goal of this approach was to ensure that small capable models were trained with data focused on high quality and advanced reasoning. |
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phi-4 underwent a rigorous enhancement and alignment process, incorporating both supervised fine-tuning and direct preference optimization to ensure precise instruction adherence and robust safety measures |
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Architecture |
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14B parameters, dense decoder-only Transformer model |
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Inputs |
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- |
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Text, best suited for prompts in the chat format |
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Context length |
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- |
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16K tokens |
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GPUs |
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- |
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1920 H100-80G |
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Training time |
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21 days |
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Training data |
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9.8T tokens |
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Outputs |
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Generated text in response to input |
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Dates |
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- |
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October 2024 – November 2024 |
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Status |
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Static model trained on an offline dataset with cutoff dates of June 2024 and earlier for publicly available data |
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Release date |
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- |
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December 12, 2024 |
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License |
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- |
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MIT |
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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-Q8_0-GGUF --hf-file phi-4-q8_0.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-Q8_0-GGUF --hf-file phi-4-q8_0.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-Q8_0-GGUF --hf-file phi-4-q8_0.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-Q8_0-GGUF --hf-file phi-4-q8_0.gguf -c 2048 |
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``` |
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