GPT-2 to GPT-5.5 Distilled 25K: Instruction-Response Pairs for Advanced Reasoning

25,000 unique, high-quality instruction-response pairs designed for knowledge distillation and supervised fine-tuning. The dataset aims to transfer frontier reasoning capabilities from a hypothetical GPT-5.5 teacher into smaller models like GPT-2 Medium. It was created by author gss1147 and last updated on May 15, 2026.

Use Cases

• Supervised fine-tuning of language models based on high-quality instruction-response pairs.
• Knowledge distillation to transfer multi-step chain-of-thought reasoning capabilities.
• Training models for cross-domain synthesis tasks based on the described reasoning features.
• Benchmarking model performance on edge-case analysis and novel insight generation.

Strengths

• Contains 25,000 unique instruction-response pairs.
• Explicitly designed for transferring advanced reasoning capabilities like multi-step CoT and cross-domain synthesis.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and file size are unknown, which may limit suitability assessment.
• The description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

huggingface user gss1147

Collection Method

Likely generated via distillation from a teacher model, though the exact method is unspecified.

Freshness

Last updated 2026-05-15 04:23:36; freshness should be verified.