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README.md
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# Model Card for AllyArc
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This model card describes AllyArc, an educational chatbot designed to support autistic students with personalized learning experiences. AllyArc uses a fine-tuned Large Language Model to interact with users and provide educational content.
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## Model Details
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### Model Description
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AllyArc is an innovative chatbot tailored for the educational support of autistic students. It leverages a fine-tuned LLM to provide interactive learning experiences, emotional support, and a platform for students to engage in conversational learning.
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- **Developed by:** Zainab, a computer science student and MLH Top 50.
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- **Funded by [optional]:** Grants/Sponsorships [More Information Needed]
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- **Shared by [optional]:** Educational institutions [More Information Needed]
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- **Model type:** Conversational Large Language Model
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- **Language(s) (NLP):** Primarily English, with potential multilingual support.
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- **License:** [More Information Needed] - Suggest an open-source license compatible with educational use.
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- **Finetuned from model [optional]:** Base LLM, such as GPT-3.
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### Model Sources [optional]
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- **Repository:** [GitHub or other repository link]
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- **Paper [Coming Soon]:** [Link to any research paper published]
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- **Demo [Coming Soon]:** [Link to a live demo if available]
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## Uses
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### Direct Use
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AllyArc can be directly interacted with by students and educators through a conversational interface, providing instant responses to queries and aiding in learning.
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### Downstream Use [optional]
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The model can be integrated into educational platforms or applications as a support tool for autistic students, offering personalized assistance.
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### Out-of-Scope Use
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AllyArc is not designed for high-stakes decisions, medical advice, or any context outside of educational support.
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## Bias, Risks, and Limitations
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While designed to be inclusive, there is a risk of unintended bias in responses due to the training data. The model may not fully understand or appropriately respond to all nuances of human emotion and communication.
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### Recommendations
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Educators should monitor interactions and provide regular feedback to improve AllyArc's accuracy and sensitivity. Users should be aware of the model's limitations and not rely on it for critical decisions.
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## How to Get Started with the Model
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To begin working with AllyArc, access the interactive Colab notebook which provides a guided experience:
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[AllyArc Interactive Colab Notebook](https://colab.research.google.com/drive/1MiGTw7nKMFbE8FllpVAW66DTmQSzOTFd?usp=sharing)
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The notebook contains all the necessary instructions to initialize the model, interact with it, and understand its output. Follow the steps in the notebook to get a hands-on experience with AllyArc.
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<!--
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## Training Details
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### Training Data
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The model is trained on a curated dataset from educational websites and textbooks, with a focus on materials suitable for autistic learners.
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### Training Procedure
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#### Preprocessing [optional]
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Data is cleaned and formatted to remove irrelevant information, ensuring the model receives high-quality input.
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#### Training Hyperparameters
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- **Training regime:** fp16 mixed precision for efficiency.
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#### Speeds, Sizes, Times [optional]
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[More Information Needed]
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## Evaluation
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### Testing Data, Factors & Metrics
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#### Testing Data
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The model is evaluated against a set of questions and scenarios typical of an educational environment for autistic students.
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#### Factors
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The evaluation considers the model's ability to handle various subjects and the clarity of its explanations.
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#### Metrics
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Metrics include accuracy, response time, and user satisfaction.
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### Results
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[More Information Needed]
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#### Summary
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[More Information Needed]
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## Environmental Impact
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- **Hardware Type:** Cloud-based GPUs.
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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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The model uses a transformer-based architecture optimized for conversational understanding.
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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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**BibTeX:**
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```bibtex
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@misc{allyarc2024,
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title={AllyArc: A Conversational Chatbot for Autistic Learners},
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author={Zainab},
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year={2024},
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note={Model card for AllyArc}
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}
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```
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**APA:**
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Zainab. (2024). AllyArc: A Conversational Chatbot for Autistic Learners. [Model Card].
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## Glossary [optional]
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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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Zainab
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## Model Card Contact
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[Contact Information]
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->
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