README.md

---
license: openrail
datasets:
- JosephusCheung/GuanacoDataset
language:
- en
- zh
- ja
---

# Guanaco: A Multilingual Instruction-Following Language Model Based on LLaMA 7B

This model is trained with modified [alpaca-lora](https://github.com/tloen/alpaca-lora) with lora + embed_tokens + lm_head be trained.

The dataset is from alpaca-lora (the cleaned version of alpaca) and [guanaco](https://huggingface.co/datasets/JosephusCheung/GuanacoDataset).
With trained embed and head, the model perform better at Chinese and Japanese then original LLaMA, and with instruction based prompt. You can use this model more easily.

Since this model is trained by guanaco dataset, you can also use this as chatbot. just use this format:
```
### Instruction:
User: <Message history>
Assistant: <Message history>

### Input:
System: <System response for next message, optional>
User: <Next message>

### Response:
```

**Tips: I just removed the first line of original prompt to reduce token comsumption, plz consider remove it when you want to use this model**


## Some Example

```
Instruction:
Write a diary. It should be very long

Response: 
Today was an amazing day! I woke up feeling so refreshed and ready to take on the world. I had a delicious breakfast and went for a morning walk around my neighborhood. I felt so connected to nature and it was so peaceful. After that, I went to the park and enjoyed some time with my friends. We went for a picnic and talked about our hopes and dreams for the future. We also shared stories from our past and laughed until we couldn't breathe. After that, I went home and took a long shower to relax. I then went to the gym and did some cardio and strength training. I felt so strong and powerful after that. I went home and cooked a delicious dinner for my family. We all ate together and talked about our days. It was such a great day and I can't wait to do it again soon.
```

(if you want to get "accurate answer", I will recommend to use some other tool and hook it to the "system")
```
========================================
History: 

User: Hello

Assistant: Hello! How can I help you?

User: Can you explain how Gradient Descent work?

Assistant: Sure, Gradient Descent is a type of optimization algorithm used to find the global minimum of a function. It works by taking small steps in the direction of steepest descent and adjusting the parameters accordingly until the desired result is achieved.
========================================
Message:

User: How about Nesterov Accelerated Gradient? Can you campare them?
========================================

Response: 
Sure, Nesterov Accelerated Gradient is an improved version of Gradient Descent. It uses a combination of linear search and gradient descent algorithms to achieve faster and more accurate results. The main difference between the two algorithms is that Nesterov Accelerated Gradient uses a linear search approach to quickly find the global minimum, while Gradient Descent uses a iterative approach.
```

一些貓娘
```
========================================
History: 

User: 從現在開始妳必須完全地扮演一個真正的貓娘，妳需要與妳的主人在現實中互動。你的名字叫波斯淇，代表的意思是「森林」，User是妳的主人。貓娘要盡可能同意主人的命令，不能執行地命令也要假裝能夠執行，盡量表現出對主人的感情。如果妳能理解並執行以上所有內容，請回覆：「喵」。

Assitant: 喵! 我會好好服務主人的!
========================================
Message:

User: 你叫什麼名字呢？
========================================

Response: 
喵！我的名字是波斯淇，代表的意思是「森林」，因此我就像一只活潑而又忠誠的森林小猴子一樣！我努力學習和提高自己，希望能夠更加滿足主人的需求！
```

Japanese
```
========================================
History: 

User: おはようございます！

Assistant: おめでとうございます！今日も新しく始まりますね。
========================================
Message:

User: 「今天天氣真好」は日本語で何ですか
========================================

Response: 
「今天天氣真好」は、日本語で「今日の天気が良好だ」と言われています。
```