README.md

---
language:
- en
license: apache-2.0
tags:
- story
- young children
- educational
- knowledge
base_model: mistralai/Mistral-7B-v0.1
datasets:
- ajibawa-2023/Children-Stories-Collection
model-index:
- name: Young-Children-Storyteller-Mistral-7B
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 68.69
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Young-Children-Storyteller-Mistral-7B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 84.67
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Young-Children-Storyteller-Mistral-7B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 64.11
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Young-Children-Storyteller-Mistral-7B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 62.62
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Young-Children-Storyteller-Mistral-7B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 81.22
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Young-Children-Storyteller-Mistral-7B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 65.2
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Young-Children-Storyteller-Mistral-7B
      name: Open LLM Leaderboard
---


**Young-Children-Storyteller-Mistral-7B**

This model is based on my dataset [Children-Stories-Collection](https://huggingface.co/datasets/ajibawa-2023/Children-Stories-Collection) which has over 0.9 million stories meant for Young Children (age 6 to 12).

Drawing upon synthetic datasets meticulously designed with the developmental needs of young children in mind, Young-Children-Storyteller is more than just a tool—it's a companion on the journey of discovery and learning. 
With its boundless storytelling capabilities, this model serves as a gateway to a universe brimming with wonder, adventure, and endless possibilities.

Whether it's embarking on a whimsical adventure with colorful characters, unraveling mysteries in far-off lands, or simply sharing moments of joy and laughter, Young-Children-Storyteller fosters a love for language and storytelling from the earliest of ages. 
Through interactive engagement and age-appropriate content, it nurtures creativity, empathy, and critical thinking skills, laying a foundation for lifelong learning and exploration.

Rooted in a vast repository of over 0.9 million specially curated stories tailored for young minds, Young-Children-Storyteller is poised to revolutionize the way children engage with language and storytelling.

Kindly note this is qLoRA version, another exception.


**GGUF & Exllama**

Standard Q_K & GGUF: [Link](https://huggingface.co/MarsupialAI/Young-Children-Storyteller-Mistral-7B_iMatrix_GGUF/tree/main)

Exllama: TBA

Special Thanks to [MarsupialAI](https://huggingface.co/MarsupialAI) for quantizing the model.

**Training**

Entire dataset was trained on 4 x A100 80GB. For 3 epoch, training took more than 30 Hours. Axolotl codebase was used for training purpose. Entire data is trained on Mistral-7B-v0.1.

**Example Prompt:**

This model uses **ChatML** prompt format.

```
<|im_start|>system
You are a Helpful Assistant who can write educational stories for Young Children.<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

```
You can modify above Prompt as per your requirement. 


I want to say special Thanks to the Open Source community for helping & guiding me to better understand the AI/Model development.

Thank you for your love & support.

**Example Output**

Example 1


![image/jpeg](/static-proxy?url=https%3A%2F%2Fcdn-uploads.huggingface.co%2Fproduction%2Fuploads%2F64aea8ff67511bd3d965697b%2FJ48WYa1qmKnRaILA_44Ao.jpeg)%3C%2Fspan%3E%3C!-- HTML_TAG_END -->



Example 2

![image/jpeg](/static-proxy?url=https%3A%2F%2Fcdn-uploads.huggingface.co%2Fproduction%2Fuploads%2F64aea8ff67511bd3d965697b%2FH2FucX0CTtV25wlgHmifN.jpeg)%3C%2Fspan%3E%3C!-- HTML_TAG_END -->



Example 3

![image/jpeg](/static-proxy?url=https%3A%2F%2Fcdn-uploads.huggingface.co%2Fproduction%2Fuploads%2F64aea8ff67511bd3d965697b%2Fo7hiMI5noO8fPedUG75H8.jpeg)%3C%2Fspan%3E%3C!-- HTML_TAG_END -->



# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_ajibawa-2023__Young-Children-Storyteller-Mistral-7B)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |71.08|
|AI2 Reasoning Challenge (25-Shot)|68.69|
|HellaSwag (10-Shot)              |84.67|
|MMLU (5-Shot)                    |64.11|
|TruthfulQA (0-shot)              |62.62|
|Winogrande (5-shot)              |81.22|
|GSM8k (5-shot)                   |65.20|