Remove cold start data for collaboration
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README.md
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MIT License - see [LICENSE](LICENSE) file for details.
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I'm perfectly happy working on this solo, but collaboration can be rewarding when there's mutual value and good fit.
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### π οΈ Areas Where I'd Value Expertise
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**Distributed Sandbox Engineering:**
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- Asynchronous code execution environment with load balancing
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- Worker pool architecture for parallel code execution
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- Systems engineering and containerization expertise
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**Dataset Engineering:**
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- Mathematical reasoning dataset curation and validation
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- Cold-start data pipeline design
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- Quality control and formatting workflows
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### π Collaboration Approach
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- **Start small:** Open an issue to discuss your approach first
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- **Show, don't tell:** Small proof-of-concept before larger contributions
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- **Quality focused:** Code review and documentation required
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- **Clear attribution:** All substantial contributors get proper credit
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### π° The Compute Reality
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**Full training requires significant resources:**
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- ~8x A100s for complete AIME validation
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- Currently exploring compute sponsorship options
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- Happy to validate on smaller models first
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### π― What I'm Looking For
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- People who bring complementary skills (not just ML knowledge)
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- Contributors who can work independently and deliver quality
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- Collaborative mindset without drama or politics
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**Interested?** Open an issue with your background and what you'd like to work on. Let's see if there's a good fit!
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*No pressure though - I genuinely enjoy the solo research implementation process too.* π
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## π Acknowledgments
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MIT License - see [LICENSE](LICENSE) file for details.
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**π€ Collaboration welcome:**
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Looking for teammates with complementary skills:
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- **Systems engineers**: Distributed sandbox architecture with load balancing
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- **Compute sponsors**: Academic institutions or cloud providers for training runs
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- **Experimenters**: End-to-end validation and benchmarking on mathematical reasoning tasks
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## π Acknowledgments
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