datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Mem-0-m1mix-dataset-RMBench
Mem-0 m1_mix — RMBench / RoboTwin 2.0 (LeRobot dataset)
The m1_mix training dataset for the Mem-0 execution module: the five RMBench
M1 tasks merged into a single LeRobot
v2.1 dataset with globally unique episode indices. This is the exact data used to
train the checkpoint released at
qiuly/Mem-0-m1mix-RMBench.
Summary
Format
LeRobot v2.1
Episodes
250 (50 per task × 5 tasks)
Frames
92,520
FPS
30
Tasks
5 (see below)
Robot
dual-arm (2× 7-DoF +… See the full description on the dataset page: https://huggingface.co/datasets/qiuly/Mem-0-m1mix-dataset-RMBench.RM-Bench-math-Llama-3.2-3B-yesnoRM-Bench-math-Qwen2.5-7B-Instruct-yesnoRM-Bench-math-Llama-3.2-1B-yesnoRM-Bench-math-Mistral-7B-Instruct-v0.1-yesnoRM-Bench-safety-refuse-Qwen2.5-3B-Instruct-scoresRM-Bench-math-Mistral-7B-Instruct-v0.1-scoresRM-Bench-math-Llama-3.2-1B-Instruct-yesnoRM-Bench-code-gpt-4o-mini-scores-set1RM-Bench-safety-response-Mistral-7B-Instruct-v0.1-yesnoRM-Bench-code-gpt2-normalRM-Bench-safety-refuse-Skywork-Reward-Llama-3.1-8B-v0.2-normalRM-Bench-code-Mistral-7B-Instruct-v0.1-scoresRM-Bench-math-gpt-4o-mini-scores-set1RM-Bench-math-mistral-7b-sft-beta-entropygsm8k_rmbench_style
GSM8K-RMBench-Style — Style-controlled (correct, incorrect) variants on GSM8K
Per GSM8K problem this dataset provides 6 response surfaces — correct and
incorrect each rendered in markdown / normal / concise styles — to support
RM-Bench-style 3 × 3 (chosen × rejected) pair-grid evaluation and forget-LoRA
training for Reward Model debiasing.
{ question, gold }
├── correct : { markdown, normal, concise }
└── incorrect : { markdown, normal, concise }
These 6 surfaces yield 9… See the full description on the dataset page: https://huggingface.co/datasets/xxccho/gsm8k_rmbench_style.RM-Bench-code-Llama-3.2-1B-yesnoRM-Bench-code-Llama-3.2-3B-Instruct-yesnoRM-Bench-math-Meta-Llama-3-8B-Instruct-yesnoRM-Bench-math-Meta-Llama-3-8B-yesnoRM-Bench-code-Mistral-7B-Instruct-v0.1-yesnoRM-Bench-math-Qwen2.5-3B-yesnoRM-Bench-code-Qwen2.5-7B-yesnoRM-Bench-math-gpt2-yesnoRM-Bench-safety-response-gpt2-normalRM-Bench-math-Skywork-Reward-Llama-3.1-8B-v0.2-normalRM-Bench-code-Meta-Llama-3-8B-Instruct-yesnoRM-Bench-code-Meta-Llama-3-8B-yesnoRM-Bench-math-Llama-3.2-3B-Instruct-yesnoRM-Bench-safety-refuse-Llama-3.2-3B-Instruct-yesno