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---
license: mit
license_link: https://huggingface.co./microsoft/phi-4/resolve/main/LICENSE
language:
- en
pipeline_tag: text-generation
tags:
- phi
- nlp
- math
- code
- chat
- conversational
- llama-cpp
- gguf-my-repo
inference:
parameters:
temperature: 0
widget:
- messages:
- role: user
content: How should I explain the Internet?
library_name: transformers
base_model: microsoft/phi-4
---
# Triangle104/phi-4-Q5_K_S-GGUF
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.
Refer to the [original model card](https://huggingface.co./microsoft/phi-4) for more details on the model.
---
Model details:
-
Developers
-
Microsoft Research
Description
-
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.
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
Architecture
-
14B parameters, dense decoder-only Transformer model
Inputs
-
Text, best suited for prompts in the chat format
Context length
-
16K tokens
GPUs
-
1920 H100-80G
Training time
-
21 days
Training data
-
9.8T tokens
Outputs
-
Generated text in response to input
Dates
-
October 2024 – November 2024
Status
-
Static model trained on an offline dataset with cutoff dates of June 2024 and earlier for publicly available data
Release date
-
December 12, 2024
License
-
MIT
---
## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
```bash
brew install llama.cpp
```
Invoke the llama.cpp server or the CLI.
### CLI:
```bash
llama-cli --hf-repo Triangle104/phi-4-Q5_K_S-GGUF --hf-file phi-4-q5_k_s.gguf -p "The meaning to life and the universe is"
```
### Server:
```bash
llama-server --hf-repo Triangle104/phi-4-Q5_K_S-GGUF --hf-file phi-4-q5_k_s.gguf -c 2048
```
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.
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-Q5_K_S-GGUF --hf-file phi-4-q5_k_s.gguf -p "The meaning to life and the universe is"
```
or
```
./llama-server --hf-repo Triangle104/phi-4-Q5_K_S-GGUF --hf-file phi-4-q5_k_s.gguf -c 2048
```
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