Create README.md

README.md

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+---
+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|>
+
+```
+
+---
+
+## 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
+
+> 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<br>3.8b | Phi-2<br>2.7b | Mistral<br>7b | Gemma<br>7b | Llama-3-In<br>8b | Mixtral<br>8x7b | GPT-3.5<br>version 1106 |
+|---|---|---|---|---|---|---|---|
+| MMLU <br>5-Shot | 68.8 | 56.3 | 61.7 | 63.6 | 66.5 | 68.4 | 71.4 |
+| HellaSwag <br> 5-Shot | 76.7 | 53.6 | 58.5 | 49.8 | 71.1 | 70.4 | 78.8 |
+| ANLI <br> 7-Shot | 52.8 | 42.5 | 47.1 | 48.7 | 57.3 | 55.2 | 58.1 |
+| GSM-8K <br> 0-Shot; CoT | 82.5 | 61.1 | 46.4 | 59.8 | 77.4 | 64.7 | 78.1 |
+| MedQA <br> 2-Shot | 53.8 | 40.9 | 49.6 | 50.0 | 60.5 | 62.2 | 63.4 |
+| AGIEval <br> 0-Shot | 37.5 | 29.8 | 35.1 | 42.1 | 42.0 | 45.2 | 48.4 |
+| TriviaQA <br> 5-Shot | 64.0 | 45.2 | 72.3 | 75.2 | 67.7 | 82.2 | 85.8 |
+| Arc-C <br> 10-Shot | 84.9 | 75.9 | 78.6 | 78.3 | 82.8 | 87.3 | 87.4 |
+| Arc-E <br> 10-Shot | 94.6 | 88.5 | 90.6 | 91.4 | 93.4 | 95.6 | 96.3 |
+| PIQA <br> 5-Shot | 84.2 | 60.2 | 77.7 | 78.1 | 75.7 | 86.0 | 86.6 |
+| SociQA <br> 5-Shot | 76.6 | 68.3 | 74.6 | 65.5 | 73.9 | 75.9 | 68.3 |
+| BigBench-Hard <br> 0-Shot | 71.7 | 59.4 | 57.3 | 59.6 | 51.5 | 69.7 | 68.32 |
+| WinoGrande <br> 5-Shot | 70.8 | 54.7 | 54.2 | 55.6 | 65 | 62.0 | 68.8 |
+| OpenBookQA <br> 10-Shot | 83.2 | 73.6 | 79.8 | 78.6 | 82.6 | 85.8 | 86.0 |
+| BoolQ <br> 0-Shot | 77.6 | -- | 72.2 | 66.0 | 80.9 | 77.6 | 79.1 |
+| CommonSenseQA <br> 10-Shot | 80.2 | 69.3 | 72.6 | 76.2 | 79 | 78.1 | 79.6 |
+| TruthfulQA <br> 10-Shot | 65.0 | -- | 52.1 | 53.0 | 63.2 | 60.1 | 85.8 |
+| HumanEval <br> 0-Shot | 59.1 | 47.0 | 28.0 | 34.1 | 60.4 | 37.8 | 62.2 |
+| MBPP <br> 3-Shot | 53.8 | 60.6 | 50.8 | 51.5 | 67.7 | 60.2 | 77.8 |