Claude Sonnet Opus: High-Quality Analytical Reasoning Dataset for Language Model Training

A massive, high-quality analytical reasoning dataset built from Claude Sonnet 4.6 and Claude Opus 4.6/4.7. The dataset was created by author qsardor and was last updated on July 13, 2026. It has been forensically scrubbed of system prompts, AI personas, and roleplay to serve as a distilled engine for teaching models like Gemma 4.

Use Cases

• Fine-tuning language models for analytical reasoning based on the high-quality distilled content.
• Training instruction-following models based on the scrubbed, prompt-free structure.
• Benchmarking model reasoning performance based on the dataset's analytical nature.
• Researching knowledge distillation techniques based on the process of removing system prompts and personas.

Strengths

• Dataset is described as 'massive' and 'high-quality'.
• Data is specifically scrubbed of system prompts, AI personas, and roleplay, leaving distilled content.
• Built from outputs of advanced models Claude Sonnet 4.6 and Claude Opus 4.6/4.7.

Limitations

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

Provenance

Source

huggingface, author qsardor

Collection Method

Built from outputs of Claude Sonnet 4.6 and Claude Opus 4.6/4.7 models, with forensic scrubbing applied.

Freshness

Last updated 2026-07-13 12:51:48; freshness should be verified.