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1.7.0

ShauryaS31

Shaurya Sharma@ShauryaS31

1

Events attended

1

Submissions made

Looking for experience!

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šŸ¤ Top Collaborators

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Sajid Hameed

I am Student of software Engineering at University Of Agriculture Faisalabad. I know Machine Learning and MERN Stack,Solved 240+ Problems at LeetCode , attend Hackathons at Lablabai and Devpost.

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Tajmir Khan

As a researcher have good publications in reputable journals and substantial teaching experience. Moreover, have recorded Object-Oriented Programming (OOP) lectures on YouTube and strong coding skills, showcased in my GitHub repository. Additionally, I have experience in blogging (OOP). Besides, I participated in international hackathons. Looking ahead, Aspirant to keep working on AI/ML research and publish my work in effective journals.

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Karol Malicki

I am a last-year student with a strong passion for creating innovative solutions that drive change. With experience in a diverse technology stack, including Python, Go, Vue.js, Docker, Flutter, Kubernetes, and more, I am always eager to expand my skill set and learn new technologies. I believe in the power of collaboration and design thinking to solve complex problems. My approach emphasizes creative problem-solving and user-centered design, which is why I advocate for regular planning meetings to ensure the best solutions emerge through collective input and iterative thinking. As I approach the final stages of my academic journey, I am excited to continue developing my skills and contribute to projects that push the boundaries of technology and innovation.

šŸ¤“ Latest Submissions

    Llama Proxy

    Llama Proxy

    We propose using the LLaMA 3.1:1B model as a local proxy server to manage caches with JSON responses. Here's how the llama model can help us do just that: Query analysis and optimization Smart data management in the cache Optimization of communication with API Create intelligent cache management policies. Enrich responses and adding a layer of security and privacy to the application. Understand user behavior and tailor data to their needs. We can also approach the problem using the cloud model, when we do not have enough RAM to be able to run llama 3.1:1B. We can then send queries from time to time to the server, which would decide on the cache hierarchy, which would be the most important, and which items would already have a deletion time.

    Hackathon link

    20 Oct 2024

šŸ‘Œ Attended Hackathons

    Edge Runners 3.2

    Edge Runners 3.2

    ⌚ Take on a 48-hour challenge packed with creativity. šŸš€ Build an app powered by Llama 3.2’s capabilities. šŸŽ“ Get advice and support from industry experts along every step of the way. šŸ† Win an opportunity to participate in the Lablab NEXT acceleration program šŸ’° Stand a chance to win $5,000 in prizes. 🌟 Win the opportunity to be invited, with transport and accommodation covered, to our upcoming Giga Hackathons in Barcelona or Geneva in partnership with UNICEF. šŸ§‘šŸ»ā€šŸ’» Sign up before the Kick-Off Stream to lock in your spot!

šŸ“ Certificates

    Edge Runners 3.2

    Edge Runners 3.2 | Certificate

    View Certificate