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Training Example Metadata — Exact Row Duplicates Validator
x402
Training Example Metadata — Exact Row Duplicates Validator is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).
Detects and reports exact duplicate rows in a training example metadata CSV, validating up to 1000 rows against a declared table contract.
Price / call$0.01
Success—
StatusUnknown
How this service works
Training example metadata — Exact row duplicates: Exact row duplicates for Training example metadata. Validate a declared CSV table contract, up to 1000 rows. Quoted cells supported; no external enrichment. Specialised preset in a shared 50-profile, 20-operation engine. 0.01 USDC includes one CSV exact row duplicates report.
Output
A report identifying all exact duplicate rows within the submitted CSV, including which rows are duplicated and how many times, validated against the declared table contract (allowed categories, value ranges, cell length limits) for up to 1000 rows.
Example use cases
Pre-training data deduplication check
“Before I kick off my model training run, can you scan this training metadata CSV for any exact duplicate rows? The file uses comma separators and the valid label categories are class-0 and class-1.”
ML pipeline data quality audit
“I need to audit my training example metadata for data quality — specifically, flag any rows that appear more than once in this CSV. The delimiter is a tab and allowed categories are positive, negative, and neutral.”
Dataset integrity validation for experiment
“Can you validate this training data CSV and produce an exact row duplicate report? The CSV uses semicolons as delimiters, max cell length should be 500, and the allowed categories are group-a, group-b, and group-c.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-bx-csv-training-data-duplicate-rows?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to specifically identify exact duplicate rows in a training example metadata CSV as part of a data quality or validation pipeline. It is purpose-built for training data schemas with fields like example_id, label, and sample_weight, and operates entirely offline with no external enrichment. Prefer it over general-purpose deduplication tools when you want a low-cost ($0.01 USDC), fast, contract-aware validation report scoped to ML training data.
Side effects
- CSV exceeds 1000 rows — only up to 1000 rows are supported
- CSV string exceeds 100,000 character limit
- Invalid delimiter specified outside of comma, semicolon, or tab
- Cell content exceeds max_cell_length limit
- Malformed CSV that cannot be parsed
- Category values not matching allowed_categories list
- Numeric values outside specified minimum/maximum bounds
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| csv | string | |
| maximum | number | |
| minimum | number | |
| delimiter | string | |
| max_cell_length | integer | |
| allowed_categories | array |
Tags
x402
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