# Llama3-ChatQA-1.5-8B-Llama3-8B-Chinese-Chat-linear-merge

## Models Used

- nvidia/Llama3-ChatQA-1.5-8B
- shenzhi-wang/Llama3-8B-Chinese-Chat

## Configuration

```yaml
models:
  - model: nvidia/Llama3-ChatQA-1.5-8B
    parameters:
      weight: 0.5
  - model: shenzhi-wang/Llama3-8B-Chinese-Chat
    parameters:
      weight: 0.5
merge_method: linear
parameters:
  normalize: true
dtype: float16
```
---
license: llama3
tags:
- merge
- mergekit
- lazymergekit
- Llama3-ChatQA-1.5-8B
- Llama3-8B-Chinese-Chat
---

# Llama3-ChatQA-1.5-8B-Llama3-8B-Chinese-Chat-linear-merge

Llama3-ChatQA-1.5-8B-Llama3-8B-Chinese-Chat-linear-merge is an innovative language model resulting from the strategic combination of two powerful models: [Llama3-ChatQA-1.5-8B](https://huggingface.co/nvidia/Llama3-ChatQA-1.5-8B) and [Llama3-8B-Chinese-Chat](https://huggingface.co/shenzhi-wang/Llama3-8B-Chinese-Chat). The merging process utilized [mergekit](https://github.com/mergekit), a specialized tool designed for effective model blending, ensuring optimal performance and synergy between the two architectures.

## 🧩 Merge Configuration

The models were merged using a linear interpolation method, which allows for a balanced integration of both models' capabilities. The configuration for this merge is as follows:

```yaml
models:
  - model: nvidia/Llama3-ChatQA-1.5-8B
    parameters:
      weight: 0.5
  - model: shenzhi-wang/Llama3-8B-Chinese-Chat
    parameters:
      weight: 0.5
merge_method: linear
parameters:
  normalize: true
dtype: float16
```

## Model Features

This merged model combines the conversational question-answering prowess of Llama3-ChatQA-1.5 with the bilingual capabilities of Llama3-8B-Chinese-Chat. As a result, it excels in various text generation tasks, including but not limited to:

- Conversational question answering in both English and Chinese.
- Enhanced context understanding and nuanced text generation.
- Improved performance in retrieval-augmented generation (RAG) tasks.

By leveraging the strengths of both parent models, this fusion model is particularly adept at handling complex queries and generating contextually relevant responses across languages.

## Evaluation Results

The evaluation results of the parent models indicate their strong performance in various benchmarks. For instance, Llama3-ChatQA-1.5-8B has shown impressive results in the ChatRAG Bench, outperforming many existing models in conversational QA tasks. Meanwhile, Llama3-8B-Chinese-Chat has demonstrated superior performance in Chinese language tasks, surpassing ChatGPT and matching GPT-4 in various evaluations.

| Model | Average Score (ChatRAG Bench) |
|-------|-------------------------------|
| Llama3-ChatQA-1.5-8B | 55.17 |
| Llama3-8B-Chinese-Chat | Not specified, but noted for high performance |

## Limitations

While the Llama3-ChatQA-1.5-8B-Llama3-8B-Chinese-Chat-linear-merge model offers enhanced capabilities, it may also inherit some limitations from its parent models. These include:

- Potential biases present in the training data of both models, which could affect the generated outputs.
- The model's performance may vary depending on the complexity of the queries, especially in less common languages or dialects.
- As with any AI model, it may struggle with ambiguous queries or context that is not well-defined.

In summary, the Llama3-ChatQA-1.5-8B-Llama3-8B-Chinese-Chat-linear-merge model represents a significant advancement in multilingual conversational AI, combining the best features of its predecessors while also carrying forward some of their limitations.