README.md

---
base_model: unsloth/Meta-Llama-3.1-8B-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- gguf
---

# Model Description

This model is a fine-tuned version of [unsloth/Meta-Llama-3.1-8B-bnb-4bit](https://huggingface.co/unsloth/Meta-Llama-3.1-8B-bnb-4bit) on [cognitivecomputations/Code-290k-ShareGPT-Vicuna](https://huggingface.co/datasets/cognitivecomputations/Code-290k-ShareGPT-Vicuna) in order to answer questions related to programming better. Trained by the [Google Colab Notebook](https://colab.research.google.com/drive/1NYMWMe2Q11fQI3r6bPmOEbQd73sG9GW1?usp=sharing) provided by Unsloth with small modifications.
Dataset format was converted from ShareGPT to [Llama 3](https://llama.meta.com/docs/model-cards-and-prompt-formats/meta-llama-3/) in the training notebook. First 10k rows was used in training for demonstration purposes.
- **Developed by:** [Can Deniz Koçak](https://www.linkedin.com/in/candenizkocak/)
- **Finetuned from model:** [unsloth/Meta-Llama-3.1-8B-bnb-4bit](https://huggingface.co/unsloth/Meta-Llama-3.1-8B-bnb-4bit)


### Fine-tuning Data

[cognitivecomputations/Code-290k-ShareGPT-Vicuna](https://huggingface.co/datasets/cognitivecomputations/Code-290k-ShareGPT-Vicuna)

### Training Procedure

Trained on a single A100 on Google Colab.
<a target="_blank" href="https://colab.research.google.com/drive/1NYMWMe2Q11fQI3r6bPmOEbQd73sG9GW1?usp=sharing">
  <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>
- **Developed by:** candenizkocak
- **License:** apache-2.0
- **Finetuned from model :** unsloth/Meta-Llama-3.1-8B-bnb-4bit

This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.

[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)