datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
gpt-5.2-high-reasoning-250x
Generated using DataGen by TeichAI
This is a reasoning dataset created using GPT 5.2 with a reasoning depth set to high.
The dataset is meant for creating distilled versions of GPT 5.2 by fine-tuning already existing open-source LLMs.
Stats
Costs: $ 10.58 (USD)
Total tokens (input + output): N\A
Sonnet-Opus-4.5-4.6-Gemini-3.0-3.1-Pro-GPT-5-5.1-5.2-GLM-4.7-MiniMax-M2.1-DeepSeek-V3.2-High
Distill
This is a multi-source curated instruction and reasoning dataset specifically for training and distilling large language models (LLMs) to exhibit advanced Chain-of-Thought (CoT), Agentic, Mathematical and Coding capabilities. It aggregates high-quality outputs from frontier models into messages ChatML format.
Dataset Structure
The dataset contains a total of 70.2K examples, split into three subsets based on the presence of visible reasoning… See the full description on the dataset page: https://huggingface.co/datasets/VINAY-UMRETHE/Sonnet-Opus-4.5-4.6-Gemini-3.0-3.1-Pro-GPT-5-5.1-5.2-GLM-4.7-MiniMax-M2.1-DeepSeek-V3.2-High.v3-2k-traj-gpt-5.2swebench-verified-gpt-5.2btc-reasoning-traces-gpt5.2
BTC Reasoning Traces — gpt-5.2-chat-latest
LLM reasoning traces for BTC/USD trading decisions. Each row is one hourly
trading decision: the model receives account state + multi-timeframe OHLCV
market data, reasons step-by-step in <think> tags, and outputs a discrete
action (<answer>N</answer>). The dataset stores the full chain-of-thought
alongside the resulting reward and next state — making it suitable for
offline RL, imitation learning, or reward modelling.
Generation… See the full description on the dataset page: https://huggingface.co/datasets/Torch-Trade/btc-reasoning-traces-gpt5.2.qgqa-gpt-5.2-20260213-041705qgqa-final5-full-20260225-004316-gpt-5.2-2025-12-11arc-barc-processed-direct-max4k-gpt5.2abstractions-rubrics-0114-3of32arc-barc-processed-direct-max4k-summaries-abs-gpt5.2-test-qwensols-21of24arc-barc-processed-direct-max4k-summaries-abs-gpt5.2-test-qwensols-22of24arc-barc-processed-direct-max4k-gpt5.2abstractions-rubrics-0114-28of32arc-barc-processed-direct-max4k-gpt5.2abstractions-rubrics-0114-20of32arc-direct-gpt5.2abstractions-rephrased-sft-oracle-trlarc-barc-processed-direct-max4k-gpt5.2abstractions-rephrased-partial0.4-qwensols-0104arc-barc-processed-direct-max4k-gpt5.2abstractions-rubrics-0114-19of32arc-barc-processed-direct-max4k-gpt5.2abstractions-rubrics-0114-13of32arc-barc-processed-direct-max4k-gpt5.2abstractions-rubrics-0114-15of32arc-barc-processed-direct-max4k-gpt5.2abstractions-rubrics-0114-24of32qgqa-unified-processed-gpt-5.2-20260213-033916gpt-5.2_v2arc-barc-processed-direct-max4k-summaries-abs-gpt5.2-test-qwensols-16of24arc-barc-processed-direct-max4k-summaries-abs-gpt5.2-test-qwensolsarc-barc-processed-direct-max4k-gpt5.2abstractions-rephrased-partial0.2-0104-6of8arc-barc-processed-direct-max4k-gpt5.2abstractions-rubrics-0114-25of32arc-barc-processed-direct-max4k-gpt5.2abstractions-rubrics-0114-26of32arc-barc-processed-direct-max4k-gpt5.2abstractions-rubrics-0114-10of32arc-barc-processed-direct-max4k-gpt5.2abstractions-rubrics-0114-4of32arc-barc-processed-direct-max4k-gpt5.2abstractions-rubrics-0114-5of32arc-barc-processed-direct-max4k-gpt5.2abstractions-rubrics-0114-23of32arc-barc-processed-direct-max4k-gpt5.2abstractions-rubrics-0114-14of32