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name: text-and-tabular description: "Operate AutoTrain Advanced text, NLP, sentence-transformers, extractive QA, and tabular training workflows." disable-model-invocation: true metadata: disco-role: operating parent-skill: autotrain-advanced license: Apache 2.0

AutoTrain text, NLP, embeddings, and tabular workflows

Use this sub-skill for non-LLM text tasks, sentence-transformers, extractive QA, and tabular workflows.

Supported entry points

• autotrain text-classification --help
• autotrain text-regression --help
• autotrain token-classification --help
• autotrain seq2seq --help
• autotrain sentence-transformers --help
• autotrain tabular --help
• autotrain extractive-qa --help
• YAML aliases such as text-classification, text-regression, token-classification, seq2seq, extractive-qa, sentence-transformers:pair, st:triplet, and tabular

If the request is LLM-specific, route to ../llm-training/; the data validator in this sub-skill still supports --task llm for local column checks.

Task families

Family	Typical data shape	Notes
text classification/regression	text column + target/label column	Binary and multi-class classification resolve to the same text-classification trainer family.
token classification	token list column + tag list column	Values may be Python-list strings that AutoTrain parses with ast.literal_eval.
seq2seq	source text + target text	Use for summarization/translation-style data.
extractive QA	context text + question + answer dict/string	Answer values should be dict-like or parseable into dicts.
sentence-transformers	pair/triplet/QA rows	Trainer variants control whether target labels/scores are needed.
tabular	id column + one or more target columns	task distinguishes classification vs regression.

Safe validation sequence

1. Inspect the specific command help with the root inspect_cli.py helper.
2. Validate YAML configs with the root validate_config.py helper.
3. Validate local CSV/JSONL columns with scripts/validate_text_data.py.
4. Launch training only after model, data path, split names, backend, and Hub credentials are confirmed.

Useful script

python skills/disco/autotrain-advanced/sub-skills/text-and-tabular/scripts/validate_text_data.py \
  --task text-classification \
  --text-column text \
  --target-column label \
  data.csv

The script performs local schema checks only. It does not import trainer code, upload data, or start training.

References

• references/workflows.md — task/alias map and command/config patterns.
• references/data-formats.md — column schemas and validator examples.
• references/troubleshooting.md — column mapping, parser, Hub, and local dataset recovery.