---
language:
  - en
license: apache-2.0
datasets:
  - HuggingFaceH4/ultrachat_200k
  - Felladrin/ChatML-ultrachat_200k
  - Open-Orca/OpenOrca
  - Felladrin/ChatML-OpenOrca
  - hkust-nlp/deita-10k-v0
  - Felladrin/ChatML-deita-10k-v0
  - LDJnr/Capybara
  - Felladrin/ChatML-Capybara
  - databricks/databricks-dolly-15k
  - Felladrin/ChatML-databricks-dolly-15k
  - euclaise/reddit-instruct-curated
  - Felladrin/ChatML-reddit-instruct-curated
  - CohereForAI/aya_dataset
  - Felladrin/ChatML-aya_dataset
base_model: Locutusque/TinyMistral-248M
pipeline_tag: text-generation
widget:
  - 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?
  - messages:
      - role: user
        content: Heya!
      - role: assistant
        content: Hi! How may I help you?
      - role: user
        content:
          I'm 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: system
        content: You are a very creative assistant. User will give you a task, which you should complete with all your knowledge.
      - role: user
        content: Hello! Can you please elaborate a background story of an RPG game about wizards and dragons in a sci-fi world?
inference:
  parameters:
    max_new_tokens: 250
    penalty_alpha: 0.5
    top_k: 5
---

# Locutusque's TinyMistral-248M trained on chat datasets

- Base model: [Locutusque/TinyMistral-248M](https://huggingface.co/Locutusque/TinyMistral-248M) with two additional special tokens (`<|im_start|>` and `<|im_end|>`)
- Datasets:
  - [[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-OpenOrca)] [Open-Orca/OpenOrca](https://huggingface.co/datasets/Open-Orca/OpenOrca)
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-deita-10k-v0)] [hkust-nlp/deita-10k-v0](https://huggingface.co/datasets/hkust-nlp/deita-10k-v0)
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-Capybara)] [LDJnr/Capybara](https://huggingface.co/datasets/LDJnr/Capybara)
  - [[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-aya_dataset)] [CohereForAI/aya_dataset](https://huggingface.co/datasets/CohereForAI/aya_dataset)
- License: [Apache License 2.0](https://huggingface.co/Felladrin/TinyMistral-248M-Chat-v2/resolve/main/license.txt)

## Recommended Prompt Format

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

## Recommended Inference Parameters

```yml
penalty_alpha: 0.5
top_k: 5
```

## Usage Example

```python
from transformers import pipeline

generate = pipeline("text-generation", "Felladrin/TinyMistral-248M-Chat-v2")

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,
    penalty_alpha=0.5,
    top_k=5,
)

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

## How it was trained

This model was trained with [SFTTrainer](https://huggingface.co/docs/trl/main/en/sft_trainer) using the following settings:

| Hyperparameter         | Value                                         |
| :--------------------- | :-------------------------------------------- |
| Learning rate          | 2e-5                                          |
| Total train batch size | 32                                            |
| Max. sequence length   | 2048                                          |
| Weight decay           | 0.01                                          |
| Warmup ratio           | 0.1                                           |
| NEFTune Noise Alpha    | 5                                             |
| Optimizer              | Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| Scheduler              | cosine                                        |
| Seed                   | 42                                            |