SaaS Metrics
Gemini Executive Synthesis
Helios's training data availability.
Technical Positioning
A 'Real Real-Time Long Video Generation Model.'
SaaS Insight & Market Implications
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.
Proprietary Technical Taxonomy
Raw Developer Origin & Technical Request
GitHub Issue
Apr 2, 2026
Repo: PKU-YuanGroup/Helios
Is it possible to make the training data available?
Hello! Thank you very much for your inspiring work. I would like to ask: is there any possibility that you could make your training data publicly available?
Developer Debate & Comments
No active discussions extracted for this entry yet.
Adjacent Repository Pain Points
Other highly discussed features and pain points extracted from PKU-YuanGroup/Helios.
参考图加噪问题
2
Extracted Positioning
Helios's training process, specifically the noise application to reference image `x0` during Stage 1.
A real-time long video generation model.
Extracted Positioning
Helios-Base speed comparison and the impact of `Multi-Term Memory Patchification` on T2V tasks.
A 'Real Real-Time Long Video Generation Model' emphasizing speed.
Extracted Positioning
Helios model training strategies: `is_amplify_history` and `restrict_self_attn`.
A real-time long video generation model.
Top Replies
@Iriya99 感谢关注！请使用`merge_lora_for_helios.py`进行代码合并。 https://github.com/PKU-YuanGroup/Helios/blob/main/tools/merge_lora_for_helios.py
> [@Iriya99](https://github.com/Iriya99) 感谢关注！请使用`merge_lora_for_helios.py`进行代码合并。 https://github.com/PKU-YuanGroup/Helios/blob/main/tools/merge_lora_for_helios.py transformer和pipe...
pipe填wan或者helios的路径都行。transformer得看你训练的时候用了哪个transformer，比如stage-1-init用的是wan的transformer，此时填wan的路径，其他阶段以此类推。
Top Replies
排除代码/权重加载问题前提下，训练一开始是这样的，往后训会逐渐连贯。你这个大概训了多久？batchsize和lr分别是多少？
您好，我训练了8000step, batchsize1，lr固定5e-5
bs有点小，可以试着把`random_drop_t2v_ratio`关小，不然模型没学多少v2v任务
Frequently Asked Questions
Market intelligence mapped to Helios's training data availability..
What is the technical positioning of Helios's training data availability.?
Based on our AI analysis of the original developer request, its primary technical positioning is: A 'Real Real-Time Long Video Generation Model.'
How is the developer community reacting to Helios's training data availability.?
Yes, we have tracked 1 direct responses and active debates regarding this specific topic originating from GitHub Issue.
Which technical concepts are associated with Helios's training data availability.?
Our proprietary extraction maps Helios's training data availability. to adjacent architectural concepts including training data publicly available.
How does the GitHub community build with Helios's training data availability.?
Yes, open-source adoption is correlated. An active project titled 'PKU-YuanGroup/Helios' explores similar frameworks: Helios: Real Real-Time Long Video Generation Model
Engagement Signals
Cross-Market Term Frequency
Quantifies the cross-market adoption of foundational terms like training data publicly available by tracking occurrence frequency across active SaaS architectures and enterprise developer debates.