PKU-YuanGroup/Helios

This issue is a direct request for Helios's training data to be made publicly available. This reflects a common developer need for transparency and reproducibility in AI model development. Access to training data is crucial for researchers to understand model biases, replicate results, and potentially fine-tune models for specific use cases. For B2B SaaS, while proprietary training data can be a competitive advantage, making subsets or anonymized versions available can foster community engagement, accelerate research, and build trust. The decision to share or withhold training data has significant implications for ecosystem development and the broader adoption of the model in academic and commercial settings.