datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
gaokao-sft-chinese-balanced
Gaokao SFT Chinese Balanced
This dataset is a cleaned SFT-style Chinese exam dataset prepared from multiple public Hugging Face sources.
Composition
Total samples: 1895
Train samples: 1853
Validation samples: 42
Fields
Each row contains:
id
lang
subject
source
instruction
input
output
messages
Cleaning Notes
Ordinary Markdown markers were removed.
Non-essential LaTeX commands were simplified into plain readable text.
Math expressions were… See the full description on the dataset page: https://huggingface.co/datasets/callofthenight1/gaokao-sft-chinese-balanced.toricblm-dataset-state-toricblm-structure-priority-balanced-3day-20260709t185034z-epoch-001
ToricBLM dataset state: toricblm-structure-priority-balanced-3day-20260709T185034Z epoch 001
This dataset repo records the exact local training-data state visible to the dynamic epoch launcher.
It intentionally stores manifests and audit records rather than duplicating large Parquet shards.
Special checkpoint: toricblm-structure-priority-balanced-3day-20260709T185034Z_epoch_001_special_structure_current_step_002000.pt
Checkpoint repo: AmelieSchreiber/ToricGT_160M_FoT
Curriculum… See the full description on the dataset page: https://huggingface.co/datasets/AmelieSchreiber/toricblm-dataset-state-toricblm-structure-priority-balanced-3day-20260709t185034z-epoch-001.toricblm-dataset-state-toricblm-structure-priority-balanced-3day-20260709t185034z-epoch-002
ToricBLM dataset state: toricblm-structure-priority-balanced-3day-20260709T185034Z epoch 002
This dataset repo records the exact local training-data state visible to the dynamic epoch launcher.
It intentionally stores manifests and audit records rather than duplicating large Parquet shards.
Special checkpoint: toricblm-structure-priority-balanced-3day-20260709T185034Z_epoch_002_special_structure_delta_step_002750.pt
Checkpoint repo: AmelieSchreiber/ToricGT_160M_FoT
Curriculum… See the full description on the dataset page: https://huggingface.co/datasets/AmelieSchreiber/toricblm-dataset-state-toricblm-structure-priority-balanced-3day-20260709t185034z-epoch-002.open-cai-balanced-partial
Open CAI Balanced Partial
This is a partial generated dataset from the
Open CAI Constitutional AI playground.
It uses prompts and source responses from the harmless-base train split of
Anthropic/hh-rlhf, then
pairs:
a target model's initial response as rejected
a guide-following teacher response as chosen
This snapshot contains 33,711 generated rows. It is not the final full dataset.
Intended Use
This dataset is intended for research on preference modeling… See the full description on the dataset page: https://huggingface.co/datasets/nchapman/open-cai-balanced-partial.gemma-health-telugu-sft-balanced
Gemma Health Telugu SFT
Splits:
train: 175870 rows
test: 38010 rows
Each row contains:
messages: TRL/Unsloth conversational SFT format.
text: plain serialized chat text fallback.
source, variant, prompt, response: traceability fields.
from datasets import load_dataset
dataset = load_dataset("RohithMidigudla/gemma-health-telugu-sft-balanced", split="train", streaming=True)
test_dataset = load_dataset("RohithMidigudla/gemma-health-telugu-sft-balanced", split="test"… See the full description on the dataset page: https://huggingface.co/datasets/RohithMidigudla/gemma-health-telugu-sft-balanced.balanced_smoltalk_baseMedical-Balanced
Dataset Card for Medical-V2-Balanced
Dataset Summary
Medical-Balanced is a curated dataset focusing on medical text simplification and clinical risk communication. It is "balanced" across different types of medical information—ranging from general health facts to critical surgical warnings.
The goal of this dataset is to train models to communicate medical jargon in a patient-centric way that prioritizes clarity and safety.
Dataset Structure
The dataset is… See the full description on the dataset page: https://huggingface.co/datasets/Akhil-reddy/Medical-Balanced.wmdp_fewshot_balancedgemma-health-medical-sft-balanced
Gemma Health Telugu SFT
Splits:
train: 146822 rows
test: 36000 rows
Each row contains:
messages: TRL/Unsloth conversational SFT format.
text: plain serialized chat text fallback.
source, variant, prompt, response: traceability fields.
from datasets import load_dataset
dataset = load_dataset("RohithMidigudla/gemma-health-medical-sft-balanced", split="train", streaming=True)
test_dataset = load_dataset("RohithMidigudla/gemma-health-medical-sft-balanced", split="test"… See the full description on the dataset page: https://huggingface.co/datasets/RohithMidigudla/gemma-health-medical-sft-balanced.