README.md

---
license: apache-2.0
tags:
- moe
- merge
- mergekit
- lazymergekit
- Felladrin/Minueza-32M-Base
- Felladrin/Minueza-32M-UltraChat
datasets:
- Skylion007/openwebtext
- c4
- wikimedia/wikipedia
- tiiuae/falcon-refinedweb
- izumi-lab/open-text-books
- togethercomputer/RedPajama-Data-V2
- databricks/databricks-dolly-15k
- euclaise/reddit-instruct-curated
- CohereForAI/aya_dataset
- HuggingFaceH4/ultrachat_200k
- Felladrin/ChatML-ultrachat_200k
pipeline_tag: text-generation
widget:
- messages:
  - role: user
    content: Specs of a game about trolls and warriors in a fantasy world.
- messages:
  - role: user
    content: Reducing waste generation is essential to...
- messages:
  - role: user
    content: Water, planet, resource, future
- messages:
  - role: user
    content: Background story of an RPG game about wizards and dragons in a sci-fi
      world. The story takes place in a...
- messages:
  - role: system
    content: You are a career counselor. The user will provide you with an individual
      looking for guidance in their professional life, and your task is to assist
      them in determining what careers they are most suited for based on their skills,
      interests, and experience. You should also conduct research into the various
      options available, explain the job market trends in different industries, and
      advice on which qualifications would be beneficial for pursuing particular fields.
  - role: user
    content: Heya!
  - role: assistant
    content: Hi! How may I help you?
  - role: user
    content: I am interested in developing a career in software engineering. What
      would you recommend me to do?
- messages:
  - role: user
    content: Morning!
  - role: assistant
    content: Good morning! How can I help you today?
  - role: user
    content: Could you give me some tips for becoming a healthier person?
- messages:
  - role: user
    content: Write the specs of a game about mages in a fantasy world.
- messages:
  - role: user
    content: Tell me about the pros and cons of social media.
- messages:
  - role: system
    content: You are a highly knowledgeable and friendly assistant. Your goal is to
      understand and respond to user inquiries with clarity. Your interactions are
      always respectful, helpful, and focused on delivering the most accurate information
      to the user.
  - role: user
    content: Hey! Got a question for you!
  - role: assistant
    content: Sure! What's it?
  - role: user
    content: What are some potential applications for quantum computing?
---

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# Mixnueza-6x32M-MoE

Mixnueza-6x32M-MoE is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* 3 X [Felladrin/Minueza-32M-Base](https://huggingface.co/Felladrin/Minueza-32M-Base)
* 3 X [Felladrin/Minueza-32M-UltraChat](https://huggingface.co/Felladrin/Minueza-32M-UltraChat)
* [Evaluation Results](https://huggingface.co/datasets/open-llm-leaderboard/details_Isotonic__Mixnueza-6x32M-MoE)

## Recommended Prompt Format

```
<|im_start|>system
{system_message}<|im_end|>
<|im_start|>user
{user_message}<|im_end|>
<|im_start|>assistant
```

## Recommended Inference Parameters

```yml
do_sample: true
temperature: 0.65
top_p: 0.55
top_k: 35
repetition_penalty: 1.176
```

## Usage Example

```python
from transformers import pipeline

generate = pipeline("text-generation", "Felladrin/Minueza-32M-UltraChat")

messages = [
    {
        "role": "system",
        "content": "You are a highly knowledgeable and friendly assistant. Your goal is to understand and respond to user inquiries with clarity. Your interactions are always respectful, helpful, and focused on delivering the most accurate information to the user.",
    },
    {
        "role": "user",
        "content": "Hey! Got a question for you!",
    },
    {
        "role": "assistant",
        "content": "Sure! What's it?",
    },
    {
        "role": "user",
        "content": "What are some potential applications for quantum computing?",
    },
]

prompt = generate.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)

output = generate(
    prompt,
    max_new_tokens=256,
    do_sample=True,
    temperature=0.65,
    top_k=35,
    top_p=0.55,
    repetition_penalty=1.176,
)

print(output[0]["generated_text"])
```