datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
PokerBench
PokerBench Overview
This dataset contains natural language game scenarios and optimal decisions computed by solvers in No Limit Texas Hold’em. It is divided into pre-flop and post-flop datasets, each with training and test splits. The data is stored in both .json and .csv formats:
JSON files: Contain the natural language prompts (instruction) and optimal decisions (output) derived from the game scenarios.
CSV files: Contain structured game information from which the JSON files… See the full description on the dataset page: https://huggingface.co/datasets/RZ412/PokerBench.PokerBench
PokerBench Overview
This dataset contains natural language game scenarios and optimal decisions computed by solvers in No Limit Texas Hold’em. It is divided into pre-flop and post-flop datasets, each with training and test splits. The data is stored in both .json and .csv formats:
JSON files: Contain the natural language prompts (instruction) and optimal decisions (output) derived from the game scenarios.
CSV files: Contain structured game information from which the JSON files… See the full description on the dataset page: https://huggingface.co/datasets/WhiteWatson/PokerBench.pokerbench-rl-dpo
PokerBench RL — Counterfactual DPO Preference Data
DPO preference pairs and raw self-play logs for training a Texas Hold'em LLM
to exploit non-GTO opponents, addressing the PokerBench paper's Future Work observation that pure SFT models lose to GPT-4-style "donking" strategies.
This dataset feeds the ianlee1996/pokerbench-qwen3-14b-lora-dpo checkpoint training.
How it was built
Self-play (5000 hands): ianlee1996/pokerbench-qwen3-14b-lora-mixed (Qwen3-14B + LoRA… See the full description on the dataset page: https://huggingface.co/datasets/ianlee1996/pokerbench-rl-dpo.pokerbench-8max-reasoning-traces
PokerBench 8-max — teacher-distilled reasoning traces
Reasoning traces for 8-max No-Limit Hold'em decisions, distilled from Claude
Sonnet 5 on Bedrock in the STaR style, for training small models to reason
about poker prices rather than pattern-match to an action.
Method
The teacher is not told the answer. It reasons freely from the same prompt
production sends, and a trace is kept only if its conclusion matches the target
label. Telling the teacher the target… See the full description on the dataset page: https://huggingface.co/datasets/ianlee1996/pokerbench-8max-reasoning-traces.PokerBenchExpanded