uygarkurt_-_llama-3-merged-linear-gguf/README.md

Quantization made by Richard Erkhov.

[Github](https://github.com/RichardErkhov)

[Discord](https://discord.gg/pvy7H8DZMG)

[Request more models](https://github.com/RichardErkhov/quant_request)


llama-3-merged-linear - GGUF
- Model creator: https://huggingface.co/uygarkurt/
- Original model: https://huggingface.co/uygarkurt/llama-3-merged-linear/


| Name | Quant method | Size |
| ---- | ---- | ---- |
| [llama-3-merged-linear.Q2_K.gguf](https://huggingface.co/RichardErkhov/uygarkurt_-_llama-3-merged-linear-gguf/blob/main/llama-3-merged-linear.Q2_K.gguf) | Q2_K | 2.96GB |
| [llama-3-merged-linear.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/uygarkurt_-_llama-3-merged-linear-gguf/blob/main/llama-3-merged-linear.IQ3_XS.gguf) | IQ3_XS | 3.28GB |
| [llama-3-merged-linear.IQ3_S.gguf](https://huggingface.co/RichardErkhov/uygarkurt_-_llama-3-merged-linear-gguf/blob/main/llama-3-merged-linear.IQ3_S.gguf) | IQ3_S | 3.43GB |
| [llama-3-merged-linear.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/uygarkurt_-_llama-3-merged-linear-gguf/blob/main/llama-3-merged-linear.Q3_K_S.gguf) | Q3_K_S | 3.41GB |
| [llama-3-merged-linear.IQ3_M.gguf](https://huggingface.co/RichardErkhov/uygarkurt_-_llama-3-merged-linear-gguf/blob/main/llama-3-merged-linear.IQ3_M.gguf) | IQ3_M | 3.52GB |
| [llama-3-merged-linear.Q3_K.gguf](https://huggingface.co/RichardErkhov/uygarkurt_-_llama-3-merged-linear-gguf/blob/main/llama-3-merged-linear.Q3_K.gguf) | Q3_K | 3.74GB |
| [llama-3-merged-linear.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/uygarkurt_-_llama-3-merged-linear-gguf/blob/main/llama-3-merged-linear.Q3_K_M.gguf) | Q3_K_M | 3.74GB |
| [llama-3-merged-linear.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/uygarkurt_-_llama-3-merged-linear-gguf/blob/main/llama-3-merged-linear.Q3_K_L.gguf) | Q3_K_L | 4.03GB |
| [llama-3-merged-linear.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/uygarkurt_-_llama-3-merged-linear-gguf/blob/main/llama-3-merged-linear.IQ4_XS.gguf) | IQ4_XS | 4.18GB |
| [llama-3-merged-linear.Q4_0.gguf](https://huggingface.co/RichardErkhov/uygarkurt_-_llama-3-merged-linear-gguf/blob/main/llama-3-merged-linear.Q4_0.gguf) | Q4_0 | 4.34GB |
| [llama-3-merged-linear.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/uygarkurt_-_llama-3-merged-linear-gguf/blob/main/llama-3-merged-linear.IQ4_NL.gguf) | IQ4_NL | 4.38GB |
| [llama-3-merged-linear.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/uygarkurt_-_llama-3-merged-linear-gguf/blob/main/llama-3-merged-linear.Q4_K_S.gguf) | Q4_K_S | 4.37GB |
| [llama-3-merged-linear.Q4_K.gguf](https://huggingface.co/RichardErkhov/uygarkurt_-_llama-3-merged-linear-gguf/blob/main/llama-3-merged-linear.Q4_K.gguf) | Q4_K | 4.58GB |
| [llama-3-merged-linear.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/uygarkurt_-_llama-3-merged-linear-gguf/blob/main/llama-3-merged-linear.Q4_K_M.gguf) | Q4_K_M | 4.58GB |
| [llama-3-merged-linear.Q4_1.gguf](https://huggingface.co/RichardErkhov/uygarkurt_-_llama-3-merged-linear-gguf/blob/main/llama-3-merged-linear.Q4_1.gguf) | Q4_1 | 4.78GB |
| [llama-3-merged-linear.Q5_0.gguf](https://huggingface.co/RichardErkhov/uygarkurt_-_llama-3-merged-linear-gguf/blob/main/llama-3-merged-linear.Q5_0.gguf) | Q5_0 | 5.21GB |
| [llama-3-merged-linear.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/uygarkurt_-_llama-3-merged-linear-gguf/blob/main/llama-3-merged-linear.Q5_K_S.gguf) | Q5_K_S | 5.21GB |
| [llama-3-merged-linear.Q5_K.gguf](https://huggingface.co/RichardErkhov/uygarkurt_-_llama-3-merged-linear-gguf/blob/main/llama-3-merged-linear.Q5_K.gguf) | Q5_K | 5.34GB |
| [llama-3-merged-linear.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/uygarkurt_-_llama-3-merged-linear-gguf/blob/main/llama-3-merged-linear.Q5_K_M.gguf) | Q5_K_M | 5.34GB |
| [llama-3-merged-linear.Q5_1.gguf](https://huggingface.co/RichardErkhov/uygarkurt_-_llama-3-merged-linear-gguf/blob/main/llama-3-merged-linear.Q5_1.gguf) | Q5_1 | 5.65GB |
| [llama-3-merged-linear.Q6_K.gguf](https://huggingface.co/RichardErkhov/uygarkurt_-_llama-3-merged-linear-gguf/blob/main/llama-3-merged-linear.Q6_K.gguf) | Q6_K | 6.14GB |
| [llama-3-merged-linear.Q8_0.gguf](https://huggingface.co/RichardErkhov/uygarkurt_-_llama-3-merged-linear-gguf/blob/main/llama-3-merged-linear.Q8_0.gguf) | Q8_0 | 7.95GB |




Original model description:
---
library_name: transformers
license: mit
---

# LLM Model Merging

## YouTube Tutorial
<div align="center">
    <a href="https://youtu.be/gNXBp3wttFU">Model Merging: Merge LLMs to Create Frankestein Models - Python, HuggingFace, Mergekit</a>
    <br>
    <br>
    <a href="https://youtu.be/gNXBp3wttFU">
        <img src="./thumbnail1-button.png" height="85%" width="85%%"/>
    </a>
</div>

## GitHub
You can find the GitHub from here; https://github.com/uygarkurt/Model-Merge

In this specific case, I typed `llama-3` into the open LLM leaderboard, took the best 3 models, merged them and created
a better ranking model wihtout any training.

As the main libraries we will be using [mergekit](https://github.com/arcee-ai/mergekit).

<br/>
<div align="center">
    <a href="">
        <img alt="open-source-image"
		src="https://img.shields.io/badge/%E2%9D%A4%EF%B8%8F_Open_Source-%2350C878?style=for-the-badge"/>
    </a>
    <a href="https://youtu.be/gNXBp3wttFU">
        <img alt="youtube-tutorial"
        src="https://img.shields.io/badge/YouTube_Tutorial-grey?style=for-the-badge&logo=YouTube&logoColor=%23FF0000"/>
    </a>
    <a href="https://github.com/uygarkurt/Model-Merge">
      <img alt="github-image"
      src="https://img.shields.io/badge/github-%23121011.svg?style=for-the-badge&logo=github&logoColor=white"
    </a>
</div>