datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
kimi-k2.6-reap-observations-v1
Kimi-K2.6 REAP Observation Data (v1)
Per-layer expert routing + activation statistics captured from moonshotai/Kimi-K2.6
under the REAP layerwise observer (PR #17, CerebrasResearch/reap).
What this is
This dataset contains the observer output of a full REAP calibration pass on
Kimi-K2.6. It is not a pruned model. Each record describes per-token routing
decisions, expert activation norms, and the REAP saliency ingredients for every
MoE layer of the base model.
Downstream… See the full description on the dataset page: https://huggingface.co/datasets/mateowilliam/kimi-k2.6-reap-observations-v1.kimi-k2.6-reap-observations-v1
Kimi-K2.6 REAP Observation Data (v1)
Per-layer expert routing + activation statistics captured from moonshotai/Kimi-K2.6
under the REAP layerwise observer (PR #17, CerebrasResearch/reap).
What this is
This dataset contains the observer output of a full REAP calibration pass on
Kimi-K2.6. It is not a pruned model. Each record describes per-token routing
decisions, expert activation norms, and the REAP saliency ingredients for every
MoE layer of the base model.… See the full description on the dataset page: https://huggingface.co/datasets/0xSero/kimi-k2.6-reap-observations-v1.combined-reasoning-opus-4.6-opus-4.7-kimi-k2.5-kimi-k2.6-glm-5.1
Combined Reasoning Distill — Multi-Model
A large-scale unified reasoning dataset combining thinking and chain-of-thought traces distilled from frontier models, normalized into a single consistent schema for fine-tuning. Includes data from Claude (Opus 4.5/4.6/4.7, Sonnet 4.5/4.6, Haiku 4.5), GPT (5.1/5.2), Gemini 3 Pro Preview, Kimi (K2/K2.5/K2.6), GLM (4.6/4.7/5.1), MiniMax M2.1, Grok Code Fast 1, and more.
Schema
Every row has a single field:
Field
Type… See the full description on the dataset page: https://huggingface.co/datasets/Avtrkrb/combined-reasoning-opus-4.6-opus-4.7-kimi-k2.5-kimi-k2.6-glm-5.1.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-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.Kimi-K2.6-Thinking-200x-Cleaned
Kimi K2.6 Thinking 200x — Cleaned
Cleaned version of uniquealexx/Kimi-K2.6-Thinking-200x.
Format — ShareGPT
Each row has a single conversations field in ShareGPT format:
{
"conversations": [
{"from": "human", "value": "Find all positive integers n such that..."},
{"from": "gpt", "value": "<thinking>
I need to find...
</thinking>
The answer is..."}
]
}
Usage with Unsloth
from datasets import load_dataset
dataset =… See the full description on the dataset page: https://huggingface.co/datasets/rex099/Kimi-K2.6-Thinking-200x-Cleaned.