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---
library_name: transformers
tags: []
---
# Tutor Moves - Math Remediation: Provide a Problem-Specific Solution Strategy
The tutor provides a strategy or next step for solving the problem.
## Message Structure
Tutor CoPilot models are trained on a message structure of 10 context messages followed by one target message with the special tokens `[PRETEXT]` and `[TEXT]` used to demarcate the context and target messages. Messages are formatted as `{speaker}: {message}`, where the speaker is one of `tutor` or `student`, and the message is a lowercased, anonymized version of the message. Names are anonymized with [Edu-ConvoKit](https://edu-convokit.readthedocs.io/en/latest/preprocessing.html#edu_convokit.preprocessors.TextPreprocessor.anonymize_known_names), replacing student and tutor names with `[student]` and `[tutor]`, respectively. Models are trained on text with the structure
```
"[PRETEXT] {context} [TEXT] {target}"
```
Tutor CoPilot models are only trained with tutor utterances as targets. A synthetic example of this structure, without the full 10 context utterances, is below.
```
[PRETEXT] tutor: hello, [student], happy to work with you today.
student: hi
tutor: today we will work on the topic "adding numbers"
...
student: the answer is 2. [TEXT] tutor: that's correct! 2 points.
```
## Model Details
### Model Description
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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## Uses
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### Direct Use
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### Recommendations
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## How to Get Started with the Model
Use the code below to get started with the model.
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## Training Details
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#### Summary
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## Environmental Impact
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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