Opus 4.6 10000X: High-Fidelity Reasoning Traces for Model Distillation

Opus 4.6 10000X is a dataset of 10,000 high-fidelity reasoning traces synthesized using the Claude Opus 4.6 model. It was created by user 'ansulev' and last updated on Hugging Face in May 2026. The dataset is designed to capture the model's internal 'Chain of Thought' and reasoning patterns.

Use Cases

• Supervised Fine-Tuning of language models based on high-fidelity reasoning traces.
• Knowledge distillation to transfer complex reasoning patterns from a large model to smaller ones.
• Training models for mathematical accuracy using structured logical deduction examples.
• Benchmarking model reasoning capabilities against the 'Chain of Thought' of Claude Opus 4.6.

Strengths

• Contains 10,000 synthesized reasoning traces.
• Specifically focuses on mathematical accuracy and structured logical deduction.
• Designed for Supervised Fine-Tuning and Distillation tasks.

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

huggingface

Collection Method

Synthesized using the Claude Opus 4.6 model.

Freshness

Last updated 2026-05-18 02:35:35; freshness should be verified.