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library_name: transformers
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# Model Card for Model ID
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## Model Details
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### 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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- **Developed by:**
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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###
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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[More Information Needed]
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### Training Procedure
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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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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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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## Model Card Contact
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---
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library_name: transformers
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license: mit
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datasets:
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- ryandt/essay_thesis_conversations
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language:
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- en
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---
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# Model Card for Model ID
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This is a quick test at building a model that engages in a more "pedagogically grounded" rhetoric when helping students brainstorm.
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It was developed in about a day as a proof of concept.
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### 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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- **Developed by:** Ryan Tannenbaum and For.Education
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- **Model type:** Llama 3.1 8B
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- **Language(s) (NLP):** English
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- **License:** MIT
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- **Finetuned from model:** Llama 3.1 8B
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Demo [optional]:** Coming soon
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## Uses
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The model uses the following formatting:
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```
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### USER: <What the user says>
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### ASSISTANT: <The bot response>
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...
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### TERMINATE
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```
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The model is programmed to "TERMINATE" the session when it reaches the end of its conversation
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## Bias, Risks, and Limitations
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This model uses an incredibly small dataset to tackle a very specific use case. It is a proof of concept.
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### Training Data
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[Essay Dataset](https://huggingface.co/datasets/ryandt/essay_thesis_conversations)
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### Training Procedure
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Trained with AutoTrain locally on 4090 card:
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#### Training Hyperparameters
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**Epochs**: 5
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**Learning Rate**: 2e-5
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**Train Batch Size**: 2
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**Mixed Precision**: fp16
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**Quantization**: int8
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## Model Card Authors [optional]
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Ryan Tannenbaum (ryandt)
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## Model Card Contact
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[Ryan Tannenbaum](mailto:[email protected])
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