Abel Abraha@abelabrahaaa558313877
2
Events attended
1
Submissions made
Ethiopia
5+ years of experience
About me
I'm a chemical engineering student with a strong interest in solving real-world problems through engineering, technology, and continuous learning. Alongside my university studies, I'm building skills in full-stack development, artificial intelligence, prompt engineering, Linux, and operating systems. I enjoy understanding how complex systems work, whether they're industrial processes, software, or human behavior. I'm committed to disciplined self-improvement and believe that consistent effort compounds into meaningful results. My goals are to become a skilled engineer, build impactful technology, contribute to innovation across Africa, and keep expanding my knowledge through hands-on projects, research, and lifelong learning. Current focus: • Chemical Engineering • Full-Stack Development • Artificial Intelligence & Prompt Engineering • Linux and Operating Systems • Problem Solving and Systems Thinking • Personal Development and High Performance I strive to learn, build, and create solutions that have a lasting impact.
🤝 Top Collaborators
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🤓 Latest Submissions
Jarvis limited edition 2026
HybridRoute is a token-efficient routing agent built for the 8 published capability categories: factual knowledge, math reasoning, sentiment classification, summarization, named entity recognition, code debugging, logical reasoning, and code generation. The core idea: local inference costs zero tokens on the leaderboard, so a quantized Qwen2.5-3B model bundled directly in the Docker image handles sentiment, summarization, and named entity recognition, all categories verified correct through repeated real-prompt testing. Categories needing precise multi-step reasoning or syntactic correctness (factual knowledge, math, logic, code debugging, code generation) route to Fireworks, using MiniMax M3 for reasoning-heavy tasks and Kimi K2.7 Code for programming tasks, chosen per category through direct side-by-side accuracy and token-cost comparison rather than assumption. The agent includes a fallback chain if a preferred model fails or returns an empty response, and every remote call is capped with a category-specific token budget tuned from real failure cases encountered during testing, including a bug where models silently truncated answers while reasoning internally despite explicit instructions not to. The full pipeline was validated end-to-end under the actual 4GB RAM / 2 vCPU grading constraints before submission, with repeated clean runs confirming stability.
13 Jul 2026
