Dataficial

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  Dataficial Docker Extension

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  Generated Dataset

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  Finetuning using Generated Dataset

Inspiration

The inspiration behind Dataficial from the increasing demand for high-quality datasets in the field of AI and machine learning. Recognizing the challenges developers face in generating diverse and comprehensive datasets, especially for fine-tuning language models, we set out to create a solution that seamlessly integrates into developers' workflows.

What it does

Dataficial is a Docker Desktop extension designed to simplify the process of generating synthetic datasets for the fine-tuning of language models and machine learning algorithms. It provides an intuitive interface that allows developers to customize and generate datasets with ease, ensuring diversity, relevance, and scalability.

How we built it

Reading Docker Extension Documentation (it's really helpful). The extension is constructed using a combination of containerization techniques, user-friendly front-end design (React MUI), and back-end (NodeJS and Python), I also use OpenAI to generate the data.

Challenges we ran into

Nothing so far, only limited time.

Accomplishments that we're proud of

Successfully generated synthetic dataset with only a single prompt.

What we learned

Building Docker Dekstop Extension is not as hard as I thought before.

What's next for Dataficial

Publish to Extension Marketplace (currently still in my localhost), My vision is to make Dataficial a go-to tool for developers seeking high-quality synthetic datasets to fine-tune their language models and machine learning algorithms.

Built With

• docker
• node.js
• openai
• python
• react