license: apache-2.0
General-Stories-Mistral-7B
This model is based on my dataset 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: TBA
Exllama: TBA
Training
Entire dataset was trained on 4 x A100 80GB. For 2 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.<|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
Example 2
Example 3
Example 4
