| --- |
| language: |
| - en |
| license: apache-2.0 |
| tags: |
| - information-extraction |
| - json |
| - rag |
| - structured-data |
| - synthetic |
| - legacy-database-modernization |
| task_categories: |
| - text-generation |
| - feature-extraction |
| size_categories: |
| - 1B<n<10B |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: "data/train-*.parquet" |
| --- |
| |
| # Helios Nano JSON Data |
|
|
| Large-scale synthetic dataset for training small language models (SLMs) on |
| **structured information extraction** — converting unstructured text into JSON. |
|
|
| ## Purpose |
|
|
| Designed for fine-tuning a 400M-parameter extraction engine that: |
| - Reads unstructured business documents (invoices, medical records, contracts, etc.) |
| - Follows a provided JSON schema |
| - Outputs clean, structured JSON |
|
|
| Ideal for **legacy database modernization** and **RAG pipelines**. |
|
|
| ## Dataset Structure |
|
|
| Each row contains: |
|
|
| | Column | Type | Description | |
| |---|---|---| |
| | `industry` | string | Source industry (finance, healthcare, hr, legal, …) | |
| | `doc_type` | string | Document type (invoice, prescription, contract, …) | |
| | `schema_json` | string | JSON schema the model should extract | |
| | `raw_text` | string | Unstructured source document | |
| | `extracted_json` | string | Gold-standard structured extraction | |
|
|
| ## Coverage |
|
|
| **16 industries**, **41 document types**, including: |
| - Finance: invoices, receipts, payroll, wire transfers, tax summaries, bank transactions |
| - Healthcare: patient records, prescriptions, lab results, referrals |
| - HR: employee records, job postings, performance reviews |
| - Legal: contract summaries |
| - Real Estate: property listings, lease agreements |
| - Logistics: shipping notices, purchase orders, inventory, customs declarations |
| - Retail: orders, returns |
| - Insurance: claims |
| - Education: enrollment, scholarships |
| - Manufacturing: quality inspections, maintenance logs |
| - Government: business licenses, building permits |
| - And more… |
|
|
| ## Format Diversity |
|
|
| Text fields use randomized formatting for dates (`Sept 29` / `09-29-2024` / |
| `2024-09-29`), currency (`$1,234.56` / `USD 1234.56`), phone numbers, IDs, |
| and document layout (formal headers vs. narrative prose vs. email style). |
|
|
| ## Stats |
|
|
| - **Shards**: 26 |
| - **Disk size**: 12.2 GB (Snappy-compressed Parquet) |
| - **Target**: 10B tokens (BPE, vocab 32768) |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("respinosamena/Helios-Nano-JSON-Data", split="train") |
| print(ds[0]) |
| ``` |
|
|
| ## Training Prompt Format |
|
|
| ``` |
| <|schema|>{schema_json}<|end_turn|> |
| <|document|>{raw_text}<|end_turn|> |
| <|extract|>{extracted_json}<|end_turn|> |
| ``` |
|
|
| ## License |
|
|
| Apache 2.0 |
|
|
