---
license: apache-2.0
base_model: Felladrin/Minueza-32M-Base
pipeline_tag: text-generation
language:
  - en
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
widget:
  - text: |-
      <|im_start|>system
      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.<|im_end|>
      <|im_start|>user
      Heya!<|im_end|>
      <|im_start|>assistant
      Hi! How may I help you?<|im_end|>
      <|im_start|>user
      I am interested in developing a career in software engineering. What would you recommend me to do?<|im_end|>
      <|im_start|>assistant
  - text: |-
      <|im_start|>system
      You are a highly knowledgeable assistant. Help the user as much as you can.<|im_end|>
      <|im_start|>user
      How I can become a healthier person?<|im_end|>
      <|im_start|>assistant
  - text: |-
      <|im_start|>system
      You are a helpful assistant who gives creative responses.<|im_end|>
      <|im_start|>user
      Write the specs of a game about mages in a fantasy world.<|im_end|>
      <|im_start|>assistant
  - text: |-
      <|im_start|>system
      You are a helpful assistant who answers user's questions with details.<|im_end|>
      <|im_start|>user
      Tell me about the pros and cons of social media.<|im_end|>
      <|im_start|>assistant
  - text: |-
      <|im_start|>system
      You are a helpful assistant who answers user's questions with details and curiosity.<|im_end|>
      <|im_start|>user
      What are some potential applications for quantum computing?<|im_end|>
      <|im_start|>assistant
inference:
  parameters:
    max_new_tokens: 250
    do_sample: true
    temperature: 0.7
    top_p: 0.5
    top_k: 35
    repetition_penalty: 1.176
---

# Minueza-32M-Chat: A chat model with 32 million parameters

- Base model: [Felladrin/Minueza-32M-Base](https://huggingface.co/Felladrin/Minueza-32M-Base)
- Datasets used during SFT:
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-databricks-dolly-15k)] [databricks/databricks-dolly-15k](https://huggingface.co/datasets/databricks/databricks-dolly-15k)
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-reddit-instruct-curated)] [euclaise/reddit-instruct-curated](https://huggingface.co/datasets/euclaise/reddit-instruct-curated)
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-WebGLM-QA)] [THUDM/webglm-qa](https://huggingface.co/datasets/THUDM/webglm-qa)
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-webGPT_x_dolly)] [starfishmedical/webGPT_x_dolly](https://huggingface.co/datasets/starfishmedical/webGPT_x_dolly)
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-Capybara)] [LDJnr/Capybara](https://huggingface.co/datasets/LDJnr/Capybara)
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-SlimOrca-Dedup)] [Open-Orca/SlimOrca-Dedup](https://huggingface.co/datasets/Open-Orca/SlimOrca-Dedup)
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-ultrachat_200k)] [HuggingFaceH4/ultrachat_200k](https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k)
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-HelpSteer)] [nvidia/HelpSteer](https://huggingface.co/datasets/nvidia/HelpSteer)
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-oasst2_curated)] [sablo/oasst2_curated](https://huggingface.co/datasets/sablo/oasst2_curated)
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-aya_dataset)] [CohereForAI/aya_dataset](https://huggingface.co/datasets/CohereForAI/aya_dataset)
- Datasets used during DPO:
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-distilabel-capybara-dpo-7k-binarized)] [argilla/distilabel-capybara-dpo-7k-binarized](https://huggingface.co/datasets/argilla/distilabel-capybara-dpo-7k-binarized)
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-distilabel-intel-orca-dpo-pairs)] [argilla/distilabel-intel-orca-dpo-pairs](https://huggingface.co/datasets/argilla/distilabel-intel-orca-dpo-pairs)
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-ultrafeedback-binarized-preferences)] [argilla/ultrafeedback-binarized-preferences](https://huggingface.co/datasets/argilla/ultrafeedback-binarized-preferences)
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-oasst2_dpo_pairs_en)] [sablo/oasst2_dpo_pairs_en](https://huggingface.co/datasets/sablo/oasst2_dpo_pairs_en)
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-Neural-DPO)] [NeuralNovel/Neural-DPO](https://huggingface.co/datasets/NeuralNovel/Neural-DPO)
- Availability in other ML formats:
  - GGUF: [Felladrin/gguf-Minueza-32M-Chat](https://huggingface.co/Felladrin/gguf-Minueza-32M-Chat)
  - ONNX: [Felladrin/onnx-Minueza-32M-Chat](https://huggingface.co/Felladrin/onnx-Minueza-32M-Chat)

## 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: 0.7
top_p: 0.5
top_k: 35
repetition_penalty: 1.176
```

## Usage Example

```python
from transformers import pipeline

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

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=0.7,
    top_k=35,
    top_p=0.5,
    repetition_penalty=1.176,
)

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

## License

This model is licensed under the [Apache License 2.0](https://huggingface.co/Felladrin/Minueza-32M-Chat/resolve/main/license.txt).