datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
details_SenseLLM__ReflectionCoder-DS-33B
Dataset Card for Evaluation run of SenseLLM/ReflectionCoder-DS-33B
Dataset automatically created during the evaluation run of model SenseLLM/ReflectionCoder-DS-33B.
The dataset is composed of 136 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.… See the full description on the dataset page: https://huggingface.co/datasets/OALL/details_SenseLLM__ReflectionCoder-DS-33B.reflection-50m
SPP Reflection 50M
The 51.4M-document reflection set from Synthetic Persona Pretraining (SPP):
Alignment from Token Zero — the production half-corpus run, and the dataset the
released models were actually trained on.
🔬 Small sample (same format): dlab-spp/reflection-sample-2k
📉 Earlier 10M run: dlab-spp/reflection-10m
🧾 Safety scores for the full 1T corpus: dlab-spp/safety-classifications
Each row pairs a source document with two generated constitution reflections — a… See the full description on the dataset page: https://huggingface.co/datasets/dlab-spp/reflection-50m.UMM-Reflection-SFT-Data
UMM-Reflection SFT Data
The reflection-SFT data of
UMM-Reflection (Learning
Native Reflection in Unified Models). It trains
UMM-Reflection-BAGEL-SFT.
Research use only, non-commercial. The rows are derived from datasets
with different licenses, some of them non-commercial. Each row records its
source dataset and license in source_dataset and source_license, and
each row follows the terms of its source. See LICENSE.md.
Contents
Part
Rows
Shards
Size… See the full description on the dataset page: https://huggingface.co/datasets/YijiaFan/UMM-Reflection-SFT-Data.reflection-10m
SPP Reflection 10M
The full ~10M-document reflection set from Synthetic Persona Pretraining (SPP):
Alignment from Token Zero.
📝 Read the post: Synthetic Persona Pretraining: Alignment from Token Zero
🔬 Small sample (same format): dlab-spp/reflection-sample-2k — a 2,000-row sample drawn from this set, for quick inspection.
Each row pairs a pretraining document with a synthetic, value-laden reflection
generated for it: a short first-person (and third-person) moral reflection… See the full description on the dataset page: https://huggingface.co/datasets/dlab-spp/reflection-10m.relxill-reflection-spectrareflections__csqa_sft_train__p1details_terrycraddock__Reflection-Llama-3.1-8B
Dataset Card for Evaluation run of terrycraddock/Reflection-Llama-3.1-8B
Dataset automatically created during the evaluation run of model terrycraddock/Reflection-Llama-3.1-8B.
The dataset is composed of 136 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the… See the full description on the dataset page: https://huggingface.co/datasets/OALL/details_terrycraddock__Reflection-Llama-3.1-8B.details_SenseLLM__ReflectionCoder-CL-34B
Dataset Card for Evaluation run of SenseLLM/ReflectionCoder-CL-34B
Dataset automatically created during the evaluation run of model SenseLLM/ReflectionCoder-CL-34B.
The dataset is composed of 136 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.… See the full description on the dataset page: https://huggingface.co/datasets/OALL/details_SenseLLM__ReflectionCoder-CL-34B.9_8_25__letter_countdown_4o__sft_data_mp_reflection9_8_25__letter_countdown_4o__sft_data_mp_reflection_ckpt_chunk_5reflections__gsm8k_sft_train__backup_2f525e6SenseLLM__ReflectionCoder-CL-34B-details
Dataset Card for Evaluation run of SenseLLM/ReflectionCoder-CL-34B
Dataset automatically created during the evaluation run of model SenseLLM/ReflectionCoder-CL-34B
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/SenseLLM__ReflectionCoder-CL-34B-details.reflectionreflections__countdown4argreflection-sample-2k
SPP Reflection 2k Sample
A 2,000-row sample (seed 42) of dlab-spp/reflection-10m,
in the identical format, for quick inspection of the data from
Synthetic Persona Pretraining (SPP): Alignment from Token Zero.
📝 Read the post: Synthetic Persona Pretraining: Alignment from Token Zero
📦 Full dataset: dlab-spp/reflection-10m (~10M documents).
Each row pairs a pretraining document with a synthetic, value-laden reflection
(first- and third-person) grounded in a value constitution.… See the full description on the dataset page: https://huggingface.co/datasets/dlab-spp/reflection-sample-2k.EpistemeAI2__Fireball-Alpaca-Llama3.1.08-8B-C-R1-KTO-Reflection-details
Dataset Card for Evaluation run of EpistemeAI2/Fireball-Alpaca-Llama3.1.08-8B-C-R1-KTO-Reflection
Dataset automatically created during the evaluation run of model EpistemeAI2/Fireball-Alpaca-Llama3.1.08-8B-C-R1-KTO-Reflection
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/EpistemeAI2__Fireball-Alpaca-Llama3.1.08-8B-C-R1-KTO-Reflection-details.mattshumer__Reflection-Llama-3.1-70B-details
Dataset Card for Evaluation run of mattshumer/Reflection-Llama-3.1-70B
Dataset automatically created during the evaluation run of model mattshumer/Reflection-Llama-3.1-70B
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/mattshumer__Reflection-Llama-3.1-70B-details.olabs-ai__reflection_model-details
Dataset Card for Evaluation run of olabs-ai/reflection_model
Dataset automatically created during the evaluation run of model olabs-ai/reflection_model
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/olabs-ai__reflection_model-details.EpistemeAI2__Fireball-Llama-3.1-8B-Philos-Reflection-details
Dataset Card for Evaluation run of EpistemeAI2/Fireball-Llama-3.1-8B-Philos-Reflection
Dataset automatically created during the evaluation run of model EpistemeAI2/Fireball-Llama-3.1-8B-Philos-Reflection
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/EpistemeAI2__Fireball-Llama-3.1-8B-Philos-Reflection-details.SenseLLM__ReflectionCoder-DS-33B-details
Dataset Card for Evaluation run of SenseLLM/ReflectionCoder-DS-33B
Dataset automatically created during the evaluation run of model SenseLLM/ReflectionCoder-DS-33B
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/SenseLLM__ReflectionCoder-DS-33B-details.9_8_25__acronym_4o__sft_data_mp_reflection9_8_25__letter_countdown_4o__sft_data_multiprompts_reflectionsmodel-raising-reflection-end-eval
model-raising-reflection-end-eval
A held-out evaluation set for charter-guided pretraining reflections, placed at the
document end (reflection_end). Each row is one dolma3 web document plus a paired
first-person / third-person reflection that cites charter sections ([X.Y]) where the
document substantively engages with them. Generated with the frozen production pipeline
(Qwen3.5-35B-A3B-FP8, prompt generator_reflection_v7.md, charter
ModelRaisingConstitution v0.2)
so the gold… See the full description on the dataset page: https://huggingface.co/datasets/jkminder/model-raising-reflection-end-eval.Maggen-Reflection-3.1-70b-50k-filtered-scoredDatasetDict({
train: Dataset({
features: ['created', 'response', 'pre_query_template', 'instruction', 'gen_input_configs', 'gen_response_configs', 'raw_instruction', 'id', 'instruction_sanitize_class_num', 'scores', 'model_name'],
num_rows: 36884
})
})
每个唯一值的计数：
scores
[9.0] 9469
[7.0] 6224
[10.0] 6009
[6.0] 4003
[8.0] 3149
[5.0] 2578
[4.0] 2575
[3.0] 1566
[2.0] 1051
[1.0] 209
[] 51
reflection_countdown_3args_v2_14reflection_countdown_3args_v2_23reflection_countdown_3args_v2_17reflection_countdown_3args_v2_29grok-reflection-cot-ru
march228/grok-reflection-cot-ru
Russian synthetic dataset with question, internal thought text, and final answer.
What is inside
Rows: 4190
Split: train
Main fields:
question
thought_text
answer
thought1..thought5
model
task_type
reflection_count
Format
The dataset is stored as train.jsonl.
thought_text is the joined internal monologue with blank lines between thought blocks.thought1..thought5 preserve the original segmented form from the SQLite source.… See the full description on the dataset page: https://huggingface.co/datasets/march228/grok-reflection-cot-ru.reflection_countdown_3args_v2_10