--- 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 ***Updated with Microsoft’s [latest model changes](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/commit/4f818b18e097c9ae8f93a29a57027cad54b75304) as of July 21, 2024*** **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 3432 (revision [45f2c19](https://github.com/ggerganov/llama.cpp/commit/45f2c19cc57286eead7b232ce8028273a817aa4d)), using [autogguf](https://github.com/brittlewis12/autogguf). ### Prompt template ``` <|system|> {{system_prompt}}<|end|> <|user|> {{prompt}}<|end|> <|assistant|> ``` --- ## Download & run with [cnvrs](https://twitter.com/cnvrsai) on iPhone, iPad, and Mac! ![cnvrs.ai](https://pbs.twimg.com/profile_images/1744049151241797632/0mIP-P9e_400x400.jpg) [cnvrs](https://testflight.apple.com/join/sFWReS7K) is the best app for private, local AI on your device: - create & save **Characters** with custom system prompts & temperature settings - download and experiment with any **GGUF model** you can [find on HuggingFace](https://huggingface.co/models?library=gguf)! - make it your own with custom **Theme colors** - powered by Metal ⚡️ & [Llama.cpp](https://github.com/ggerganov/llama.cpp), with **haptics** during response streaming! - **try it out** yourself today, on [Testflight](https://testflight.apple.com/join/sFWReS7K)! - follow [cnvrs on twitter](https://twitter.com/cnvrsai) to stay up to date --- ## Original Model Evaluation Comparison of July update vs original April release: | Benchmarks | Original | June 2024 Update | |------------|----------|------------------| | Instruction Extra Hard | 5.7 | 6.0 | | Instruction Hard | 4.9 | 5.1 | | Instructions Challenge | 24.6 | 42.3 | | JSON Structure Output | 11.5 | 52.3 | | XML Structure Output | 14.4 | 49.8 | | GPQA | 23.7 | 30.6 | | MMLU | 68.8 | 70.9 | | **Average** | **21.9** | **36.7** | --- ### Original April release > 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 |