dialoggpt model creation #28
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Changes Made: Created chatbot_dialoggpt.ipynb for interacting with the chatbot model. Developed config.py to manage chatbot configuration settings. Added environment.yaml for setting up a consistent Conda environment. Authored README.md with brief project setup, usage, and features. Contributor: Varun Muralidharan - Developer and architect of the chatbot components. New Components/Features: -Jupyter Notebook for Chatbot: Serves as the primary interface for the chatbot. -Configuration Management: Facilitates chatbot settings adjustments via config.py. -Environment Management: Ensures reproducibility of the development environment through environment.yaml. Enhanced Components/Features: Not applicable, as all components are newly created. Other Changes/Fixes: None, as these are new developments for the project. Additional Notes: Future steps include fine-tuning the chatbot model to better suit its intended elderly audience. TODOs: Fine-tune the chatbot model to improve response quality. Expand the dataset with more varied interactions related to elderly care.
| Ensure you have Python 3.8 or higher installed, along with pip for managing packages. | ||
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| ### dataset | ||
| Data used for training: concatenated_data.csv |
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What is the provenance (original source) of this training file? Do we have permission to use it? Do we have permission to redistribute it?
| Data used for training: concatenated_data.csv | ||
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| ## model | ||
| This is the most advanced dialoggpt model available in the public library which uses transformers algorithm for its training. Eventough the model is created to chat in a casual manner, this program has customised the model to suit the requirements of the project. |
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Which public library? What is the origin of this model? What licence is it released under?
ben-AI-cybersec
requested changes
Oct 30, 2024
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What's the utility of this file? Why are you using Linear SVC for a chatbot?
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| ## model | ||
| This is the most advanced dialoggpt model available in the public library which uses transformers algorithm for its training. Eventough the model is created to chat in a casual manner, this program has customised the model to suit the requirements of the project. | ||
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How should the user run this model? You've included a chat.py but also 3 jupyter notebooks? What does each notebook do differently?
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A lot more documentation and explanation needed, please reopen if you work on this further. |
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