richarderkhov/ajibawa-2023_-_young-children-storyteller-mistral-7b-gguf overview

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    "summary": "Detailed results can be found here |             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|",
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    "readme_markdown": "Quantization made by Richard Erkhov.\n\n[Github](https://github.com/RichardErkhov)\n\n[Discord](https://discord.gg/pvy7H8DZMG)\n\n[Request more models](https://github.com/RichardErkhov/quant_request)\n\n\nYoung-Children-Storyteller-Mistral-7B - GGUF\n- Model creator: https://huggingface.co/ajibawa-2023/\n- Original model: https://huggingface.co/ajibawa-2023/Young-Children-Storyteller-Mistral-7B/\n\n\n| Name | Quant method | Size |\n| ---- | ---- | ---- |\n| [Young-Children-Storyteller-Mistral-7B.Q2_K.gguf](https://huggingface.co/RichardErkhov/ajibawa-2023_-_Young-Children-Storyteller-Mistral-7B-gguf/blob/main/Young-Children-Storyteller-Mistral-7B.Q2_K.gguf) | Q2_K | 2.53GB |\n| [Young-Children-Storyteller-Mistral-7B.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/ajibawa-2023_-_Young-Children-Storyteller-Mistral-7B-gguf/blob/main/Young-Children-Storyteller-Mistral-7B.IQ3_XS.gguf) | IQ3_XS | 2.81GB |\n| [Young-Children-Storyteller-Mistral-7B.IQ3_S.gguf](https://huggingface.co/RichardErkhov/ajibawa-2023_-_Young-Children-Storyteller-Mistral-7B-gguf/blob/main/Young-Children-Storyteller-Mistral-7B.IQ3_S.gguf) | IQ3_S | 2.96GB |\n| [Young-Children-Storyteller-Mistral-7B.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/ajibawa-2023_-_Young-Children-Storyteller-Mistral-7B-gguf/blob/main/Young-Children-Storyteller-Mistral-7B.Q3_K_S.gguf) | Q3_K_S | 2.95GB |\n| [Young-Children-Storyteller-Mistral-7B.IQ3_M.gguf](https://huggingface.co/RichardErkhov/ajibawa-2023_-_Young-Children-Storyteller-Mistral-7B-gguf/blob/main/Young-Children-Storyteller-Mistral-7B.IQ3_M.gguf) | IQ3_M | 3.06GB |\n| [Young-Children-Storyteller-Mistral-7B.Q3_K.gguf](https://huggingface.co/RichardErkhov/ajibawa-2023_-_Young-Children-Storyteller-Mistral-7B-gguf/blob/main/Young-Children-Storyteller-Mistral-7B.Q3_K.gguf) | Q3_K | 3.28GB |\n| [Young-Children-Storyteller-Mistral-7B.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/ajibawa-2023_-_Young-Children-Storyteller-Mistral-7B-gguf/blob/main/Young-Children-Storyteller-Mistral-7B.Q3_K_M.gguf) | Q3_K_M | 3.28GB |\n| [Young-Children-Storyteller-Mistral-7B.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/ajibawa-2023_-_Young-Children-Storyteller-Mistral-7B-gguf/blob/main/Young-Children-Storyteller-Mistral-7B.Q3_K_L.gguf) | Q3_K_L | 3.56GB |\n| [Young-Children-Storyteller-Mistral-7B.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/ajibawa-2023_-_Young-Children-Storyteller-Mistral-7B-gguf/blob/main/Young-Children-Storyteller-Mistral-7B.IQ4_XS.gguf) | IQ4_XS | 3.67GB |\n| [Young-Children-Storyteller-Mistral-7B.Q4_0.gguf](https://huggingface.co/RichardErkhov/ajibawa-2023_-_Young-Children-Storyteller-Mistral-7B-gguf/blob/main/Young-Children-Storyteller-Mistral-7B.Q4_0.gguf) | Q4_0 | 3.83GB |\n| [Young-Children-Storyteller-Mistral-7B.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/ajibawa-2023_-_Young-Children-Storyteller-Mistral-7B-gguf/blob/main/Young-Children-Storyteller-Mistral-7B.IQ4_NL.gguf) | IQ4_NL | 3.87GB |\n| [Young-Children-Storyteller-Mistral-7B.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/ajibawa-2023_-_Young-Children-Storyteller-Mistral-7B-gguf/blob/main/Young-Children-Storyteller-Mistral-7B.Q4_K_S.gguf) | Q4_K_S | 3.86GB |\n| [Young-Children-Storyteller-Mistral-7B.Q4_K.gguf](https://huggingface.co/RichardErkhov/ajibawa-2023_-_Young-Children-Storyteller-Mistral-7B-gguf/blob/main/Young-Children-Storyteller-Mistral-7B.Q4_K.gguf) | Q4_K | 4.07GB |\n| [Young-Children-Storyteller-Mistral-7B.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/ajibawa-2023_-_Young-Children-Storyteller-Mistral-7B-gguf/blob/main/Young-Children-Storyteller-Mistral-7B.Q4_K_M.gguf) | Q4_K_M | 4.07GB |\n| [Young-Children-Storyteller-Mistral-7B.Q4_1.gguf](https://huggingface.co/RichardErkhov/ajibawa-2023_-_Young-Children-Storyteller-Mistral-7B-gguf/blob/main/Young-Children-Storyteller-Mistral-7B.Q4_1.gguf) | Q4_1 | 4.24GB |\n| [Young-Children-Storyteller-Mistral-7B.Q5_0.gguf](https://huggingface.co/RichardErkhov/ajibawa-2023_-_Young-Children-Storyteller-Mistral-7B-gguf/blob/main/Young-Children-Storyteller-Mistral-7B.Q5_0.gguf) | Q5_0 | 4.65GB |\n| [Young-Children-Storyteller-Mistral-7B.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/ajibawa-2023_-_Young-Children-Storyteller-Mistral-7B-gguf/blob/main/Young-Children-Storyteller-Mistral-7B.Q5_K_S.gguf) | Q5_K_S | 4.65GB |\n| [Young-Children-Storyteller-Mistral-7B.Q5_K.gguf](https://huggingface.co/RichardErkhov/ajibawa-2023_-_Young-Children-Storyteller-Mistral-7B-gguf/blob/main/Young-Children-Storyteller-Mistral-7B.Q5_K.gguf) | Q5_K | 4.78GB |\n| [Young-Children-Storyteller-Mistral-7B.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/ajibawa-2023_-_Young-Children-Storyteller-Mistral-7B-gguf/blob/main/Young-Children-Storyteller-Mistral-7B.Q5_K_M.gguf) | Q5_K_M | 4.78GB |\n| [Young-Children-Storyteller-Mistral-7B.Q5_1.gguf](https://huggingface.co/RichardErkhov/ajibawa-2023_-_Young-Children-Storyteller-Mistral-7B-gguf/blob/main/Young-Children-Storyteller-Mistral-7B.Q5_1.gguf) | Q5_1 | 5.07GB |\n| [Young-Children-Storyteller-Mistral-7B.Q6_K.gguf](https://huggingface.co/RichardErkhov/ajibawa-2023_-_Young-Children-Storyteller-Mistral-7B-gguf/blob/main/Young-Children-Storyteller-Mistral-7B.Q6_K.gguf) | Q6_K | 5.53GB |\n| [Young-Children-Storyteller-Mistral-7B.Q8_0.gguf](https://huggingface.co/RichardErkhov/ajibawa-2023_-_Young-Children-Storyteller-Mistral-7B-gguf/blob/main/Young-Children-Storyteller-Mistral-7B.Q8_0.gguf) | Q8_0 | 7.17GB |\n\n\n\n\nOriginal model description:\n---\nlanguage:\n- en\nlicense: apache-2.0\ntags:\n- story\n- young children\n- educational\n- knowledge\nbase_model: mistralai/Mistral-7B-v0.1\ndatasets:\n- ajibawa-2023/Children-Stories-Collection\nmodel-index:\n- name: Young-Children-Storyteller-Mistral-7B\n  results:\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: AI2 Reasoning Challenge (25-Shot)\n      type: ai2_arc\n      config: ARC-Challenge\n      split: test\n      args:\n        num_few_shot: 25\n    metrics:\n    - type: acc_norm\n      value: 68.69\n      name: normalized accuracy\n    source:\n      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Young-Children-Storyteller-Mistral-7B\n      name: Open LLM Leaderboard\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: HellaSwag (10-Shot)\n      type: hellaswag\n      split: validation\n      args:\n        num_few_shot: 10\n    metrics:\n    - type: acc_norm\n      value: 84.67\n      name: normalized accuracy\n    source:\n      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Young-Children-Storyteller-Mistral-7B\n      name: Open LLM Leaderboard\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: MMLU (5-Shot)\n      type: cais/mmlu\n      config: all\n      split: test\n      args:\n        num_few_shot: 5\n    metrics:\n    - type: acc\n      value: 64.11\n      name: accuracy\n    source:\n      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Young-Children-Storyteller-Mistral-7B\n      name: Open LLM Leaderboard\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: TruthfulQA (0-shot)\n      type: truthful_qa\n      config: multiple_choice\n      split: validation\n      args:\n        num_few_shot: 0\n    metrics:\n    - type: mc2\n      value: 62.62\n    source:\n      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Young-Children-Storyteller-Mistral-7B\n      name: Open LLM Leaderboard\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: Winogrande (5-shot)\n      type: winogrande\n      config: winogrande_xl\n      split: validation\n      args:\n        num_few_shot: 5\n    metrics:\n    - type: acc\n      value: 81.22\n      name: accuracy\n    source:\n      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Young-Children-Storyteller-Mistral-7B\n      name: Open LLM Leaderboard\n  - task:\n      type: text-generation\n      name: Text Generation\n    dataset:\n      name: GSM8k (5-shot)\n      type: gsm8k\n      config: main\n      split: test\n      args:\n        num_few_shot: 5\n    metrics:\n    - type: acc\n      value: 65.2\n      name: accuracy\n    source:\n      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Young-Children-Storyteller-Mistral-7B\n      name: Open LLM Leaderboard\n---\n\n\n**Young-Children-Storyteller-Mistral-7B**\n\nThis 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).\n\nDrawing 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. \nWith its boundless storytelling capabilities, this model serves as a gateway to a universe brimming with wonder, adventure, and endless possibilities.\n\nWhether 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. \nThrough interactive engagement and age-appropriate content, it nurtures creativity, empathy, and critical thinking skills, laying a foundation for lifelong learning and exploration.\n\nRooted 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.\n\nKindly note this is qLoRA version, another exception.\n\n\n**GGUF & Exllama**\n\nStandard Q_K & GGUF: [Link](https://huggingface.co/MarsupialAI/Young-Children-Storyteller-Mistral-7B_iMatrix_GGUF/tree/main)\n\nExllama: TBA\n\nSpecial Thanks to [MarsupialAI](https://huggingface.co/MarsupialAI) for quantizing the model.\n\n**Training**\n\nEntire 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.\n\n**Example Prompt:**\n\nThis model uses **ChatML** prompt format.\n\n```\n<|im_start|>system\nYou are a Helpful Assistant who can write educational stories for Young Children.<|im_end|>\n<|im_start|>user\n{prompt}<|im_end|>\n<|im_start|>assistant\n\n```\nYou can modify above Prompt as per your requirement. \n\n\nI want to say special Thanks to the Open Source community for helping & guiding me to better understand the AI/Model development.\n\nThank you for your love & support.\n\n**Example Output**\n\nExample 1\n\n\n![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64aea8ff67511bd3d965697b/J48WYa1qmKnRaILA_44Ao.jpeg)\n\n\n\nExample 2\n\n![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64aea8ff67511bd3d965697b/H2FucX0CTtV25wlgHmifN.jpeg)\n\n\n\nExample 3\n\n![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64aea8ff67511bd3d965697b/o7hiMI5noO8fPedUG75H8.jpeg)\n\n\n\n# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)\nDetailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_ajibawa-2023__Young-Children-Storyteller-Mistral-7B)\n\n|             Metric              |Value|\n|---------------------------------|----:|\n|Avg.                             |71.08|\n|AI2 Reasoning Challenge (25-Shot)|68.69|\n|HellaSwag (10-Shot)              |84.67|\n|MMLU (5-Shot)                    |64.11|\n|TruthfulQA (0-shot)              |62.62|\n|Winogrande (5-shot)              |81.22|\n|GSM8k (5-shot)                   |65.20|\n\n\n\n",
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