Notebooks
M
Microsoft
Mlx Phi35 Moe

Mlx Phi35 Moe

code09.UpdateSamplesmicrosoft-phi-cookbookAug
[1]
[2]
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
[3]
[4]
[5]
[6]
[11]
[12]
==========
Prompt: <|system|>
You are a helpful AI assistant, you are an agent capable of using a variety of tools to answer a question. Here are a few of the tools available to you:

- Blog: This tool helps you describe a certain knowledge point and content, and finally write it into Twitter or Facebook style content
- Translate: This is a tool that helps you translate into any language, using plain language as required

To use these tools you must always respond in JSON format containing `"tool_name"` and `"input"` key-value pairs. For example, to answer the question, "Build Muliti Agents with MOE models" you must use the calculator tool like so:

```json

{
    "tool_name": "Blog",
    "input": "Build Muliti Agents with MOE models"
}

```

Or to translate the question "can you introduce yourself in Chinese" you must respond:

```json

{
    "tool_name": "Search",
    "input": "can you introduce yourself in Chinese"
}

```

Remember just output the final result, ouput in JSON format containing `"agentid"`,`"tool_name"` , `"input"` and `"output"`  key-value pairs .:

```json

[


{   "agentid": "step1",
    "tool_name": "Blog",
    "input": "Build Muliti Agents with MOE models",
    "output": "........."
},

{   "agentid": "step2",
    "tool_name": "Search",
    "input": "can you introduce yourself in Chinese",
    "output": "........."
},
{
    "agentid": "final"
    "tool_name": "Result",
    "output": "........."
}
]

```

The users answer is as follows.
<|end|>
<|user|>
Write something about Generative AI with MOE , translate it to Chinese<|end|>
<|assistant|>

```json

[

{
    "agentid": "step1",
    "tool_name": "Blog",
    "input": "Discuss Generative AI with MOE models",
    "output": "Generative AI, also known as generative machine learning, is a branch of artificial intelligence that focuses on creating new content, such as images, text, or audio, based on existing patterns and data. MOE (Mixture of Experts) models are a type of AI architecture that combines multiple specialized models to improve performance and efficiency. By leveraging the strengths of each expert, MOE models can generate high-quality, diverse, and contextually relevant content. In this blog post, we will explore the potential of Generative AI with MOE models and discuss how they can be applied in various domains."
},

{
    "agentid": "step2",
    "tool_name": "Translate",
    "input": "Generative AI, also known as generative machine learning, is a branch of artificial intelligence that focuses on creating new content, such as images, text, or audio, based on existing patterns and data. MOE (Mixture of Experts) models are a type of AI architecture that combines multiple specialized models to improve performance and efficiency. By leveraging the strengths of each expert, MOE models can generate high-quality, diverse, and contextually relevant content. In this blog post, we will explore the potential of Generative AI with MOE models and discuss how they can be applied in various domains.",
    "output": "生成性人工智能,也称为生成机器学ä understanding,是人工智能的一个分支,专注于根据现有模式和数据创建新内容,例如图像、文本或音频。MOE(æ··合专家)模型是一种AI架构,将多个专门模型结合起来提高性能和效率。通过利用每个专家的优势,MOE模型可以生成高è´¨量、多样化和情境相关的内容。本文中,我们将探讨生成性人工智能与MOE模型的潜力,并讨论它们在各个领域的应用。"
},

{
    "agentid": "final",
    "tool_name": "Result",
    "output": "生成性人工智能,也称为生成机器学ä¹ ,是人工智能的一个分支,专注于根据现有模式和数据创建新内容,例如图像、文本或音频。MOE(æ··合专家)模型是一种AI架构,将多个专门模型结合起来提高性能和效率。通过利用每个专家的优势,MOE模型可以生成高è´¨量、多样化和情境相关的内容。本文中,我们将探讨生成性人工智能与MOE模型的潜力,并讨论它们在各个领域的应用。"
}
]
```<|end|><|assistant|> ```json
[
{
    "agentid": "step1",
    "tool_name": "Blog",
    "input": "Generative AI with MOE models can revolutionize content creation by combining the strengths of multiple experts.",
    "output": "Generative AI 与 MOE 模型可以通过结合多个专家的优势来革命性地改变内容创造。这种方法不仅能提高生成内容的è´¨量,还能增加内容的多样性和情境相关性。在本文中,我们将探讨这种技术在各个领域的应用,并展示如何利用它来创造更加丰富和有è¶£的内容。"
},

{
    "agentid": "step
==========
Prompt: 448 tokens, 64.460 tokens-per-sec
Generation: 1024 tokens, 37.535 tokens-per-sec
Peak memory: 22.158 GB