---
base_model: microsoft/Phi-3-mini-4k-instruct
inference: false
license: mit
license_link: https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/resolve/main/LICENSE
language:
- en
pipeline_tag: text-generation
tags:
- nlp
- code
model_creator: microsoft
model_name: Phi-3-mini-4k-instruct
model_type: phi3
quantized_by: brittlewis12
---
# Phi 3 Mini 4K Instruct GGUF
**Original model**: [Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct)
**Model creator**: [Microsoft](https://huggingface.co/microsoft)
This repo contains GGUF format model files for Microsoft’s Phi 3 Mini 4K Instruct.
> The Phi-3-Mini-4K-Instruct is a 3.8B parameters, lightweight, state-of-the-art open model trained with the Phi-3 datasets that includes both synthetic data and the filtered publicly available websites data with a focus on high-quality and reasoning dense properties.
Learn more on Microsoft’s [Model page](https://azure.microsoft.com/en-us/blog/introducing-phi-3-redefining-whats-possible-with-slms/).
### What is GGUF?
GGUF is a file format for representing AI models. It is the third version of the format,
introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp.
Converted with llama.cpp build 2721 (revision [28103f4](https://github.com/ggerganov/llama.cpp/commit/28103f4832e301a9c84d44ff0df9d75d46ab6c76)),
using [autogguf](https://github.com/brittlewis12/autogguf).
### Prompt template
```
<|system|>
{{system_prompt}}<|end|>
<|user|>
{{prompt}}<|end|>
<|assistant|>
```
---
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---
## Original Model Evaluation
> As is now standard, we use few-shot prompts to evaluate the models, at temperature 0.
> The prompts and number of shots are part of a Microsoft internal tool to evaluate language models, and in particular we did no optimization to the pipeline for Phi-3.
> More specifically, we do not change prompts, pick different few-shot examples, change prompt format, or do any other form of optimization for the model.
>
> The number of k–shot examples is listed per-benchmark.
| | Phi-3-Mini-4K-In
3.8b | Phi-2
2.7b | Mistral
7b | Gemma
7b | Llama-3-In
8b | Mixtral
8x7b | GPT-3.5
version 1106 |
|---|---|---|---|---|---|---|---|
| MMLU
5-Shot | 68.8 | 56.3 | 61.7 | 63.6 | 66.5 | 68.4 | 71.4 |
| HellaSwag
5-Shot | 76.7 | 53.6 | 58.5 | 49.8 | 71.1 | 70.4 | 78.8 |
| ANLI
7-Shot | 52.8 | 42.5 | 47.1 | 48.7 | 57.3 | 55.2 | 58.1 |
| GSM-8K
0-Shot; CoT | 82.5 | 61.1 | 46.4 | 59.8 | 77.4 | 64.7 | 78.1 |
| MedQA
2-Shot | 53.8 | 40.9 | 49.6 | 50.0 | 60.5 | 62.2 | 63.4 |
| AGIEval
0-Shot | 37.5 | 29.8 | 35.1 | 42.1 | 42.0 | 45.2 | 48.4 |
| TriviaQA
5-Shot | 64.0 | 45.2 | 72.3 | 75.2 | 67.7 | 82.2 | 85.8 |
| Arc-C
10-Shot | 84.9 | 75.9 | 78.6 | 78.3 | 82.8 | 87.3 | 87.4 |
| Arc-E
10-Shot | 94.6 | 88.5 | 90.6 | 91.4 | 93.4 | 95.6 | 96.3 |
| PIQA
5-Shot | 84.2 | 60.2 | 77.7 | 78.1 | 75.7 | 86.0 | 86.6 |
| SociQA
5-Shot | 76.6 | 68.3 | 74.6 | 65.5 | 73.9 | 75.9 | 68.3 |
| BigBench-Hard
0-Shot | 71.7 | 59.4 | 57.3 | 59.6 | 51.5 | 69.7 | 68.32 |
| WinoGrande
5-Shot | 70.8 | 54.7 | 54.2 | 55.6 | 65 | 62.0 | 68.8 |
| OpenBookQA
10-Shot | 83.2 | 73.6 | 79.8 | 78.6 | 82.6 | 85.8 | 86.0 |
| BoolQ
0-Shot | 77.6 | -- | 72.2 | 66.0 | 80.9 | 77.6 | 79.1 |
| CommonSenseQA
10-Shot | 80.2 | 69.3 | 72.6 | 76.2 | 79 | 78.1 | 79.6 |
| TruthfulQA
10-Shot | 65.0 | -- | 52.1 | 53.0 | 63.2 | 60.1 | 85.8 |
| HumanEval
0-Shot | 59.1 | 47.0 | 28.0 | 34.1 | 60.4 | 37.8 | 62.2 |
| MBPP
3-Shot | 53.8 | 60.6 | 50.8 | 51.5 | 67.7 | 60.2 | 77.8 |