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---
license: apache-2.0
tags:
- moe
- merge
- mergekit
- lazymergekit
- Felladrin/Minueza-32M-Chat
pipeline_tag: text-generation
widget:
- 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: system
    content: You are a highly knowledgeable assistant. Help the user as much as you
      can.
  - role: user
    content: How can I become a healthier person?
- messages:
  - role: system
    content: You are a helpful assistant who gives creative responses.
  - role: user
    content: Write the specs of a game about mages in a fantasy world.
- messages:
  - role: system
    content: You are a helpful assistant who answers user's questions with details.
  - role: user
    content: Tell me about the pros and cons of social media.
- messages:
  - role: system
    content: You are a helpful assistant who answers user's questions with details
      and curiosity.
  - role: user
    content: What are some potential applications for quantum computing?
inference:
  parameters:
    max_new_tokens: 250
    do_sample: true
    temperature: 0.65
    top_p: 0.55
    top_k: 35
    repetition_penalty: 1.176
datasets:
- databricks/databricks-dolly-15k
- Felladrin/ChatML-databricks-dolly-15k
- euclaise/reddit-instruct-curated
- Felladrin/ChatML-reddit-instruct-curated
- THUDM/webglm-qa
- Felladrin/ChatML-WebGLM-QA
- starfishmedical/webGPT_x_dolly
- Felladrin/ChatML-webGPT_x_dolly
- LDJnr/Capybara
- Felladrin/ChatML-Capybara
- Open-Orca/SlimOrca-Dedup
- Felladrin/ChatML-SlimOrca-Dedup
- HuggingFaceH4/ultrachat_200k
- Felladrin/ChatML-ultrachat_200k
- nvidia/HelpSteer
- Felladrin/ChatML-HelpSteer
- sablo/oasst2_curated
- Felladrin/ChatML-oasst2_curated
- CohereForAI/aya_dataset
- Felladrin/ChatML-aya_dataset
- argilla/distilabel-capybara-dpo-7k-binarized
- Felladrin/ChatML-distilabel-capybara-dpo-7k-binarized
- argilla/distilabel-intel-orca-dpo-pairs
- Felladrin/ChatML-distilabel-intel-orca-dpo-pairs
- argilla/ultrafeedback-binarized-preferences
- Felladrin/ChatML-ultrafeedback-binarized-preferences
- sablo/oasst2_dpo_pairs_en
- Felladrin/ChatML-oasst2_dpo_pairs_en
- NeuralNovel/Neural-DPO
- Felladrin/ChatML-Neural-DPO
---

🌟 Buying me coffee is a direct way to show support for this project. 
<a href="https://www.buymeacoffee.com/isotonic"><img src="https://www.buymeacoffee.com/assets/img/guidelines/download-assets-sm-1.svg" alt=""></a>

# 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):
* 6 X [Felladrin/Minueza-32M-Chat](https://huggingface.co/Felladrin/Minueza-32M-Chat)
* Num Experts Per Token : 3
* [Evaluation Results](https://huggingface.co/datasets/open-llm-leaderboard/details_Isotonic__Mixnueza-Chat-6x32M-MoE)

## 💻 Usage

```python
from transformers import pipeline

generate = pipeline("text-generation", "Isotonic/Mixnueza-6x32M-MoE")

messages = [
    {
        "role": "system",
        "content": "You are a helpful assistant who answers the user's questions with details and curiosity.",
    },
    {
        "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"])
```