| | --- |
| | license: cc-by-4.0 |
| | dataset_info: |
| | - config_name: PA-01 |
| | features: |
| | - name: patient_id |
| | dtype: string |
| | - name: image |
| | dtype: image |
| | - name: slice_index |
| | dtype: int64 |
| | - name: findings |
| | dtype: string |
| | - name: modality |
| | dtype: string |
| | splits: |
| | - name: train |
| | num_bytes: 46131453 |
| | num_examples: 527 |
| | download_size: 46109357 |
| | dataset_size: 46131453 |
| | - config_name: PA-02 |
| | features: |
| | - name: patient_id |
| | dtype: string |
| | - name: image |
| | dtype: image |
| | - name: slice_index |
| | dtype: int64 |
| | - name: findings |
| | dtype: string |
| | - name: modality |
| | dtype: string |
| | splits: |
| | - name: train |
| | num_bytes: 22736110 |
| | num_examples: 152 |
| | download_size: 22712128 |
| | dataset_size: 22736110 |
| | - config_name: PA-03 |
| | features: |
| | - name: patient_id |
| | dtype: string |
| | - name: image |
| | dtype: image |
| | - name: slice_index |
| | dtype: int64 |
| | - name: findings |
| | dtype: string |
| | - name: modality |
| | dtype: string |
| | splits: |
| | - name: train |
| | num_bytes: 41952817 |
| | num_examples: 280 |
| | download_size: 41850084 |
| | dataset_size: 41952817 |
| | - config_name: PA-04 |
| | features: |
| | - name: patient_id |
| | dtype: string |
| | - name: image |
| | dtype: image |
| | - name: slice_index |
| | dtype: int64 |
| | - name: findings |
| | dtype: string |
| | - name: modality |
| | dtype: string |
| | splits: |
| | - name: train |
| | num_bytes: 54673044 |
| | num_examples: 910 |
| | download_size: 54471985 |
| | dataset_size: 54673044 |
| | configs: |
| | - config_name: PA-01 |
| | data_files: |
| | - split: train |
| | path: PA-01/train-* |
| | - config_name: PA-02 |
| | data_files: |
| | - split: train |
| | path: PA-02/train-* |
| | - config_name: PA-03 |
| | data_files: |
| | - split: train |
| | path: PA-03/train-* |
| | - config_name: PA-04 |
| | data_files: |
| | - split: train |
| | path: PA-04/train-* |
| | tags: |
| | - medical |
| | - MRI |
| | - With_Findings |
| | - Head |
| | - brain |
| | - Spine |
| | - Joint |
| | size_categories: |
| | - 10K<n<100K |
| | --- |
| | 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: 1.6B+ words of curated STEM and Non-STEM educational content across 22000+ 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: 821K+ hours of Podcasts and Call Center data(Dual Channel) |
| | -Medical datasets: 78M+ files including clinical and diagnostic data like CT Scan, MRI, X-ray, Pathology, EHRs, USG Reports and Echo Reports. |
| | |
| | This repository includes: |
| | |
| | -A small preview subset of the Medical MRI data with 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. |
