README.md

---
license: cc-by-nc-4.0
tags:
- merge
---
### Chatty-2x8B

## Description
After some testing, finetuning and multiple merges of Llama-3 LLM models, here is something a little different.

This model is a MoE of 2x Llama-3 model trained on different RP format.

This repo contains GGUF files of Chatty-2x8B.

## The idea

I started with two separate Llama-3-Instruct-8B models, each fine-tuned for specific RP formats.

Here is two simple exemple of how it was trained.


   - **Expert 1**: This model is trained to handle RP that requires actions and descriptions between asterisks. For example:
     ```
     *nods* Yes, I understand.
     ```
   - **Expert 2**: This model is fine-tuned for plain text RP where characters’ dialogues and actions are described straightforwardly. For example:
     ```
     Nods. "Yes, I understand."
     ```

My initial idea was to make a 11B or bigger Llama-3 model, or just make a 2x8B from existing model, but I got some issues, they were not stable enough, even after DPO and FFT on top my frankenmerge/moe of Llama-3, it was not working well enough to release them.

So I just tried the idea of having 2 different RP format trained on 2 separated Llama-3-Instruct-8B, and it worked pretty well!

## The dataset

Based on Lumimaid 8B OAS success I still used the same "balance" between RP and non RP in the dataset, the maximum was 50% non RP data on each side.

RP data was different with some exception, the non RP data was exactly the same, despite that, I can't produce repetition so the double usage of non RP datasets didn't hurt the model in the end.

## Prompt template: Llama3

```
<|begin_of_text|><|start_header_id|>system<|end_header_id|>

{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>

{input}<|eot_id|><|start_header_id|>assistant<|end_header_id|>

{output}<|eot_id|>
```

## Others

Undi: If you want to support us, you can [here](https://ko-fi.com/undiai).

IkariDev: Visit my [retro/neocities style website](https://ikaridevgit.github.io/) please kek