---
library_name: transformers
license: apache-2.0
datasets:
- nampdn-ai/tiny-codes
- nlpai-lab/openassistant-guanaco-ko
- philschmid/guanaco-sharegpt-style
language:
- ko
- en
inference: false
tags:
- unsloth
- phi-3
- gguf
- ollama
pipeline_tag: text-generation
---

# Phi-3-medium-4k-instruct-ko-poc-gguf-v0.1

## Model Details

This model converted the [daekeun-ml/Phi-3-medium-4k-instruct-ko-poc-v0.1](https://huggingface.co/daekeun-ml/Phi-3-medium-4k-instruct-ko-poc-v0.1) to gguf 4-bit format. 

For detailed instructions, please refer to [Microsoft's official repo](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct-gguf).

### Dataset

The dataset used for training is as follows. To prevent catastrophic forgetting, I included non-Korean corpus as training data. Note that we did not use all of the data, but only sampled some of it. Korean textbooks were converted to Q&A format. The Guanaco dataset has been reformatted to fit the multiturn format like <|user|>\n{Q1}<|end|>\n<|assistant|>\n{A1}<|end|>\n<|user|>\n{Q2}<|end|>\n<|assistant|>\n{A2}<|end|>.

- Korean textbooks (https://huggingface.co/datasets/nampdn-ai/tiny-codes)
- Korean translation of Guanaco (https://huggingface.co/datasets/nlpai-lab/openassistant-guanaco-ko)
- Guanaco Sharegpt style (https://huggingface.co/datasets/philschmid/guanaco-sharegpt-style)

## How to Get Started with the Model using Ollama

1. **Install [Ollama](https://ollama.com/):**

```
curl -fsSL https://ollama.com/install.sh | sh
```

2. **Get the Modelfile:**

```
huggingface-cli download daekeun-ml/Phi-3-medium-4k-instruct-ko-poc-gguf-v0.1 Modelfile_q4 --local-dir /path/to/your/local/dir
```

3. **Build the Ollama Model:**
Use the Ollama CLI to create your model with the following command:

```
ollama create phi3-ko -f Modelfile_q4
```

4. **Run the model:**
```
ollama run phi3-ko What is Machine Learning?
```

## Notes 

### License

apache 2.0; The license of phi-3 is MIT, but I considered the licensing of the dataset and library used for training.

### Caution
This model was created as a personal experiment, unrelated to the organization I work for. The model may not operate correctly because separate verification was not performed. Please be careful unless it is for personal experimentation or PoC (Proof of Concept)!