datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
mimic
mimic (repack)
MIMIC-CXR-JPG 的重新打包版本，把原始的目录树（files/p1X/pXXXXXXXX/sXXXXXXXX/*.jpg）按病人分组、切成若干 parquet shard，方便整体上传/下载，同时保留精确复原原始目录结构所需的全部信息。附带的评测脚本和专家模型预测结果也放在这个 repo 里。
目录结构
.
├── p10-manifest.csv # p10 桶的文件清单（不含图像本身）
├── p10-shard-00000.parquet # p10 桶的图像数据，按 patient 分组切片
├── p10-shard-00001.parquet
├── ...
├── p11-manifest.csv
├── p11-shard-00000.parquet
├── ... # p12 ~ p19，每个桶结构相同
├── restore_from_parquet.py # 从… See the full description on the dataset page: https://huggingface.co/datasets/sunday-hao/mimic.mimir-instructionmimir-biasPubMed-Mimic-Gpt-Neoheheheh
MIMIC-Psych
MIMIC-Psych
MIMIC-Psych is a synthetic psychiatric electronic medical record (EMR) style dataset for research on clinical NLP, diagnostic decision support, and psychiatric disease classification.
The dataset contains 5,000 synthetic records and does not contain real patient-identifiable information. It is intended for academic research, benchmarking, and reproducibility support for studies on psychiatric EMR representation learning and diagnostic classification.… See the full description on the dataset page: https://huggingface.co/datasets/weihua123/MIMIC-Psych.mimic_note_summarizationallnli-mimic-embedding
ALLNLI for Mimicking Vector Space
Description
This dataset contains sentences from the ALLNLI dataset, which is a combination of the SNLI and MultiNLI datasets. It is designed for training a student model to mimic the vector space of a teacher model. This dataset is particularly useful for tasks involving embedding loss computation, where the student model learns to replicate the teacher model's embeddings. All the "anchor" and "positive" sentences from the ALLNLI… See the full description on the dataset page: https://huggingface.co/datasets/langformers/allnli-mimic-embedding.MIMIC_IV_summarization_shortsentiment140-mimic-embedding
sentiment140 for Mimicking Vector Space
Description
This dataset contains tweets from the sentiment140 dataset. It is designed for training a student model to mimic the vector space of a teacher model. This dataset is particularly useful for tasks involving embedding loss computation, where the student model learns to replicate the teacher model's embeddings.
Usage
You can load the dataset using the Hugging Face datasets library:
from datasets import… See the full description on the dataset page: https://huggingface.co/datasets/langformers/sentiment140-mimic-embedding.mimicTestMIMIC_IV_Summarization_Samplerobocasa-pnp-mimicgen
RoboCasa PnP MimicGen
This dataset contains two RoboCasa MimicGen pick-and-place datasets in the original HDF5 format:
PnPCabToCounter
PnPCounterToSink
The raw HDF5 files are stored under raw/.
Tables
metadata.csv: one row per demonstration.
actions.csv: one row per timestep with action_0 through action_11, plus timestep-level gripper joint positions.
subtasks.csv: one row per demonstration with the computed pick / place split boundary.
Subtask Split Table… See the full description on the dataset page: https://huggingface.co/datasets/kiratan/robocasa-pnp-mimicgen.MIMIC_IV_lab_testsmimicDataMIMIC_IV_lab_test_individualmimic_iv_word_countWord counts (excluding numerals and punctuation) of words from MIMIC-IV discharge summaries.
Citations
Johnson, A., Bulgarelli, L., Pollard, T., Gow, B., Moody, B., Horng, S., Celi, L. A., & Mark, R. (2024). MIMIC-IV (version 3.1). PhysioNet. RRID:SCR_007345.
annotated-mimic-cxr-reportsNanbeige4-3B-Base_blindspots
Evaluation of Nanbeige4-3B-Base: Blind Spot Analysis
Dataset: (Mimi222004/Nanbeige4-3B-Base_blindspots)
GitHub Repo: Github
Model Evaluated
Model name: Nanbeige4-3B-Base
Parameters: 3B
Type: Base causal language model
This is a base model, not instruction tuned. I selected a base model to observe raw reasoning behavior without alignment layers.
Dataset
Evaluation dataset: 25 manually constructed prompts
Correct: 16
Partial: 1
Incorrect: 8
Accuracy: 64%… See the full description on the dataset page: https://huggingface.co/datasets/Mimi222004/Nanbeige4-3B-Base_blindspots.mimic_hosp_processed_100_resampled_v2mimic10-hard-negativesnumerals_correctionMIMIC_IV_lab_test_individual