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Update model card with YAML front matter

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@@ -16,4 +16,35 @@ This repository contains a transformer model that can predict both addition and
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  ### Model-specific metadata
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  - **Operation type**: mixed
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- (Your shared text, minus YAML, goes here...)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Model-specific metadata
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  - **Operation type**: mixed
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+ # QuantaMaths: `mix_d12_l3_h4_t85K_s572091`
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+ This repository contains a transformer model that can predict both addition and subtraction questions.
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+ ### Model-specific metadata
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+ - **Operation type**: mixed
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+ - **Num digits**: 12
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+ - **Layers**: 3
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+ - **Attention Heads**: 4
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+ - **Training steps**: 85,000
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+ - **Random seed**: 572091
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+ **Contents**:
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+ - `model.pth`: The trained transformer model.
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+ - `training_loss.json`: Data gathered during model training (used to plot "loss over training batches").
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+ - `behaviors.json`: Facts gathered about the model by direct inspection (attention pattern data, PCA data, digit impact data, etc.).
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+ - `features.json`: Facts gathered about hypothesized algorithm features via experimentation, e.g. node P12L0H1 implements the feature A3.ST.
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+ **Provenance**:
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+ - `model.pth` and `training_loss.json` were created by [QuantaMathsTrain.ipynb](https://github.com/PhilipQuirke/quanta_maths/blob/main/notebooks/QuantaMathsTrain.ipynb).
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+ - `behaviors.json` and `features.json` were created by [QuantaMathsAnalyse.ipynb](https://github.com/PhilipQuirke/quanta_maths/blob/main/notebooks/QuantaMathsAnalyse.ipynb).
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+ - The JSON files are used by [QuantaMathsAlgorithm.ipynb](https://github.com/PhilipQuirke/quanta_maths/blob/main/notebooks/QuantaMathsAlgorithm.ipynb).
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+ **Folder name details**:
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+ - "add", "sub", or "mix": The types of questions the model can predict.
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+ - "d5" to "d20": How many digits the model handles (e.g. a d5 sub model can predict the answer in 123450-345670=-0123230).
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+ - "l1", "l2", or "l3": The number of layers in the model.
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+ - "h3" or "h4": The number of attention heads in the model.
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+ - "t15K" to "t85K", etc.: The number of batches the model was trained on.
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+ - "s372001", etc.: The random seed used in model training.
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