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---
language: en
license: mit
tags:
- text-generation-inference
- transformers
- Phi3
- kubernetes
base_model: unsloth/Phi-3-mini-4k-instruct
datasets:
- andyburgin/kubefix
---
# Phi-3-mini-4k-instruct-kubefix-v0.1-gguf: Fine-Tuned Phi3 for Kubernetes fault resolution
The purpose of this model is for use with [K8sGPT](https://k8sgpt.ai/) for fault analysis and resolution. Ultimately the resulting LLM is intended to be self-hosted in a GPU free environment running under [local-ai](https://localai.io/basics/kubernetes/) in Kubernetes.
The model was finetuned on [andyburgin/kubefix](https://huggingface.co/datasets/andyburgin/kubefix) which contains a series of Question and Answer pairs generated from a subset of the Kubernetes documentation from the [English markdown files](https://github.com/kubernetes/website/tree/main/content/en/docs). The Q&A pairs have been generated from the documents using an opensource model (to avoid licencing issues for some free models or SaasS services) - after much trial and error the [openchat-3.5-0106](https://huggingface.co/TheBloke/openchat-3.5-0106-GGUF) model was found to be the least problematic.
For a detailed description of the method used to generate the [andyburgin/kubefix](https://huggingface.co/datasets/andyburgin/kubefix) dataset and this model please see the [kubefix-llm repo](https://github.com/andyburgin/kubefix-llm).
**Model & Development**
- **Developed by:** andyburgin
- **License:** mit
- **Finetuned from model:** unsloth/Phi-3-mini-4k-instruct
**Key Features**
- **Kubernetes Focus:** Optimised for fault analysis for Kubernetes clusters with [K8sGPT](https://k8sgpt.ai/).
- **Knowledge Base:** Trained on a genrateed dataset from a subset of the Kubernetes documentation.
- **Text Generation:** Generates informative and potentially helpful responses.
**Important Note**
This model and dataset are under development and v0.1 is the very first release and is likely to need much optimisation and development.
**License**
This model is distributed under the MIT License
**Contributing**
Contributions are welcome to this repository! If you have improvements or suggestions, feel free to create a pull request.
**Disclaimer**
Please note - the dataset and resultant model should be considered highly experimental and used with caution, use at your own risk.
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