---
license: mit
datasets:
- flwrlabs/code-alpaca-20k
language:
- en
metrics:
- accuracy
base_model:
- microsoft/Phi-4-mini-instruct
pipeline_tag: text-generation
library_name: peft
tags:
- text-generation-inference
- code
---

> [!WARNING]
> This repository contains experimental models designed strictly for academic evaluation and research purposes.
> 
> Critical Constraints:
> * **No Production Deployment:** Experimental models must not be deployed in commercial, enterprise, or mission-critical environments under any circumstances. 
> * **No Liability:** Experimental models are provided "as-is" without warranties of any kind. The developers assume zero liability for downstream consequences, system integration failures, or regulatory non-compliance resulting from unauthorized deployment.

## Evaluation Results (Pass@1)

- **HumanEval**:  59.76 %
- **MBPP**: 46.20 %
- **MultiPL-E (C++)**: 37.27 %
- **MultiPL-E (JS)**: 52.79 %
- **Average**: 49.00 %

## Model Details

This PEFT adapter has been trained by using [Flower](https://flower.ai/), a friendly federated AI framework.

The adapter and benchmark results have been submitted to the [FlowerTune LLM Code Leaderboard](https://flower.ai/benchmarks/llm-leaderboard/code/).

Please check the following GitHub project for details on how to reproduce training and evaluation steps:

[FlowerTune-LLM-Labs](https://github.com/ethicalabs-ai/FlowerTune-LLM-Labs/blob/main/workspace/models/README.md)