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Train Local Text Baseline and Classify
x402
Train Local Text Baseline and Classify is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-12).
Trains a local naive-Bayes text classifier on up to 200 labelled records and classifies query texts into one of four educational content categories.
Price / call$0.01
Success—
StatusUnknown
How this service works
Training question - Train local text baseline and classify: Train local text baseline and classify for Training question. Up to 200 supplied labelled text records. Local dataset tools, evaluation and small naive-Bayes baselines; no hosted model or foundation-model training. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded train local text baseline and classify deliverable.
Output
Returns classification predictions for the supplied query texts, along with evaluation metrics for the locally-trained naive-Bayes model (such as accuracy or per-class performance), based on the labelled records provided as training input.
Example use cases
Classify educational course materials
“I have 50 labelled course documents tagged as concept, procedure, example, or assessment. Train a local classifier on them and then tell me which category these 5 new lesson snippets fall into.”
Baseline model for training question triage
“I want to build a quick baseline classifier that can sort student questions into concept, procedure, example, or assessment types. I have about 80 labelled examples — can you train the model and run it against my 10 test questions?”
Evaluate text label quality on small dataset
“Can you train a naive-Bayes model on my 30 labelled text records — marked as concept, procedure, example, or assessment — and tell me how well it performs so I can see if my labels are consistent?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-training-question-local-classifier?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, cheap, local text classification baseline on a small labelled dataset (up to 200 records) across the four educational content categories (concept, procedure, example, assessment) without requiring a hosted or foundation model. Ideal for rapid prototyping, label quality checks, or lightweight agentic workflows where cost matters and a naive-Bayes model is sufficient.
Side effects
- Fewer than 2 records supplied — minimum input not met
- More than 200 records supplied — exceeds maximum input limit
- Missing required fields (id, text, actual) on any record
- Invalid category value not in enum [concept, procedure, example, assessment]
- Text length exceeds 1000 character limit per record
- Empty query_texts array or more than 20 query texts supplied
- Insufficient class diversity in training records for meaningful baseline
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array | |
| query_texts | array |
Tags
x402
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