11,991 high-quality computer science literature resources and coding tasks curated by pheonix-delta. The dataset is designed to train code generation models and software agents, focusing on algorithmic logic and computer science principles. It was last updated on Hugging Face on May 24, 2026.
Use Cases
- Train code models based on curated computer science literature resources.
- Develop autocomplete tools based on algorithmic logic and coding tasks.
- Build software agents based on instruction sets teaching computer science principles.
Strengths
- 11,991 curated resources provide a substantial collection for training.
- Focus on high-quality computer science and algorithmic logic content.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- Description metadata is limited; actual data quality requires manual inspection after download.
Provenance
- Source
- pheonix-delta on Hugging Face
- Collection Method
- Curated collection
- Freshness
- Last updated 2026-05-24 17:03:40; freshness should be verified.