datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
kimi-k2.6-claude-code-tracesThis dataset was generated using teich by TeichAI
Prepare these datasets for supervised fine-tuning in just a few lines of code — see the Conversion section below.
Kimi K2.6 Claude Code Traces
This directory contains raw agent trace files generated by teich.
All assistant responses were generated by moonshotai/kimi-k2.6.
JSONL files: 36
Format
Each file is newline-delimited JSON representing a single captured agent session.
The trace schema is designed for… See the full description on the dataset page: https://huggingface.co/datasets/armand0e/kimi-k2.6-claude-code-traces.kimi-k2.6-agentThis dataset was generated using teich by TeichAI
Prepare these datasets for supervised fine-tuning in just a few lines of code — see the Conversion section below.
Kimi K2.6 Agent Traces
This directory contains raw agent trace files generated by teich.
All assistant responses were generated by moonshotai/kimi-k2.6.
JSONL files: 15
Training-ready tools
A complete configured tools schema snapshot is embedded in the collapsed section at the bottom of this README.… See the full description on the dataset page: https://huggingface.co/datasets/armand0e/kimi-k2.6-agent.Kimi-K2.6-Reasoning-3300x-WandB
Kimi-K2.6-Reasoning-3300x-WandB
Kimi-K2.6-Reasoning-3300x-WandB is a W&B-only synthetic reasoning dataset generated with Kimi-K2.6 through Weights & Biases Inference.
This dataset is the pure W&B-generated subset from a larger planned 8,000-example Kimi reasoning distillation run. Generation stopped when the W&B quota limit was reached, and the completed accepted rows were audited, cleaned, and exported as a standalone dataset.
This release contains 3,303 accepted W&B-generated rows… See the full description on the dataset page: https://huggingface.co/datasets/trjxter/Kimi-K2.6-Reasoning-3300x-WandB.Kimi-K2.6-Thinking-200x
Dataset Card (Kimi-K2.6-Thinking-200x)
Dataset Summary
Kimi-K2.6-Reasoning-207 is a high-quality distilled reasoning dataset designed for supervised fine-tuning (SFT) of small language models.
This dataset uses a curated seed question set covering Mathematics, Code, Logic, Science, Analysis, and Instruction-following domains. By calling the Kimi-K2.6 model via the Moonshot AI API as the teacher model, it generates high-quality responses featuring long-form step-by-step… See the full description on the dataset page: https://huggingface.co/datasets/uniquealexx/Kimi-K2.6-Thinking-200x.Kimi-K2.6-Technical-Reasoning-AddOn-3300x
Kimi-K2.6-Technical-Reasoning-AddOn-3300x
This dataset is a technical reasoning add-on dataset generated with Kimi K2.6 as the teacher model.
The dataset was designed as an additional technical reasoning trace set for downstream SFT experiments, especially around math, graduate-level science, coding, and debugging/code-repair style prompts.
Dataset Summary
Dataset name: Kimi-K2.6-Technical-Reasoning-AddOn-3300x
Teacher model: Kimi-K2.6
Backend: W&B… See the full description on the dataset page: https://huggingface.co/datasets/trjxter/Kimi-K2.6-Technical-Reasoning-AddOn-3300x.