metadata
license: cc-by-4.0
configs:
- config_name: PA-01_Cervical_Spine
data_files:
- split: train
path: PA-01_Cervical_Spine/train-*
- config_name: PA-02_Whole_Spine
data_files:
- split: train
path: PA-02_Whole_Spine/train-*
- config_name: PA-03_Brain
data_files:
- split: train
path: PA-03_Brain/train-*
- config_name: PA-04_Pelvic
data_files:
- split: train
path: PA-04_Pelvic/train-*
- config_name: PA-05_Right Shoulder_joint
data_files:
- split: train
path: PA-05_Right Shoulder_joint/train-*
dataset_info:
- config_name: PA-01_Cervical_Spine
features:
- name: patient_id
dtype: string
- name: image
dtype: image
- name: slice_index
dtype: int64
- name: modality
dtype: string
splits:
- name: train
num_bytes: 3547733
num_examples: 48
download_size: 3549459
dataset_size: 3547733
- config_name: PA-02_Whole_Spine
features:
- name: patient_id
dtype: string
- name: image
dtype: image
- name: slice_index
dtype: int64
- name: modality
dtype: string
splits:
- name: train
num_bytes: 11712708
num_examples: 96
download_size: 11714311
dataset_size: 11712708
- config_name: PA-03_Brain
features:
- name: patient_id
dtype: string
- name: image
dtype: image
- name: slice_index
dtype: int64
- name: modality
dtype: string
splits:
- name: train
num_bytes: 7835307
num_examples: 148
download_size: 7835138
dataset_size: 7835307
- config_name: PA-04_Pelvic
features:
- name: patient_id
dtype: string
- name: image
dtype: image
- name: slice_index
dtype: int64
- name: modality
dtype: string
splits:
- name: train
num_bytes: 14135319
num_examples: 165
download_size: 14133433
dataset_size: 14135319
- config_name: PA-05_Right Shoulder_joint
features:
- name: patient_id
dtype: string
- name: image
dtype: image
- name: slice_index
dtype: int64
- name: modality
dtype: string
splits:
- name: train
num_bytes: 6050396
num_examples: 131
download_size: 6050211
dataset_size: 6050396
size_categories:
- 100K<n<1M
The full corpus is curated across multiple STEM/Non-STEM disciplines and structured for use in LLM training, evaluation, and instruction tuning (SFT/RLHF). This sample represents the structure and quality of the larger dataset.
Dataset composition (full corpus):
-Text corpus: 1.9B+ words of curated STEM and Non-STEM educational content across 27000+ texbooks in 7 languages(English, Hindi, Arabic, Bahasa, Tamil, Telegu, Kannada)
-Question–Answer pairs: 6.5M+ high-quality Q&A pairs of STEM and Non-STEM in (English, Arabic, Hindi and Indic languages)
-Video data: 100K+ hours of STEM Videos and 30K+ hours of UGC.
-Audio data: 1M+ hours of Podcasts and Call Center data(Dual Channel)
-Medical datasets: 34M+ files including clinical and diagnostic data like CT Scan, MRI, X-ray, Pathology, EHRs, USG Reports and Echo Reports.
-Custom procurement: Dedicated team supporting any domain or language
This repository includes:
-A small preview subset of the Medical MRI data without findings.
-Flat, viewer-friendly schema for inspection
-Parquet files suitable for benchmarking and evaluation
Purpose of this dataset:
-Dataset preview and validation
-Model evaluation and experimentation
-Schema and format inspection before full-scale access
⚠️ Note: This repository contains sample data only. Access to the complete dataset is available separately under appropriate licensing or partnership terms.
Please contact
-Ph: (91)8303174762
-Em: vipul.mishra@infobay.ai
For more details.