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README.md
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# Tinystories-30m-UL2
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*GPT-4 generated model card*
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## Model Details
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- **Model Name**: GPTNeoX/flan-ul2-tinystories
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- **Model Type**: GPTNeoXForCausalLM (Language Modeling)
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- **Model Training Details**: The model is trained using [crumb/flan-ul2-tinystories](https://huggingface.co/datasets/crumb/flan-ul2-tinystories) which contains around a quarter of a million examples generated from Flan-UL2 (20b) with the prompt "Write a short story using the vocabulary of a first-grader."
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## Model Description
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This model is trained with the specific purpose of generating short narratives using a vocabulary limited to the level of a first-grader. In terms of complexity and language usage, the model is designed to produce simplistic and easily comprehensible text.
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Learning from text generated by Flan-UL2 (20b), the model adopts a simple storyline layout and a minimalistic vocabulary, which it recognizes are easier to learn and replicate.
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## Training Data
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The model is trained on the [crumb/flan-ul2-tinystories](https://huggingface.co/datasets/crumb/flan-ul2-tinystories) dataset, created with the help of Flan-UL2 (20b). The data is designed to follow the format of a simple, first-grader-level narrative, which aids the model in learning simple vocabulary and sentence structure.
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## Usage
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This model serves as a meaningful research tool in exploring the learning tendencies of smaller language models and their ability to grasp simplified language constructs. Its specific training set effectively maps the idea that a constrained vocabulary and simplistic story layouts are inherently easier to learn.
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