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Transformers Sequence Classification Pipeline

Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.

Linked challenge: NYC Rental Lease Clause Disguised Fee Anomaly Detector

Format
Code-aware
Lines
4
Sections
1
Linked challenge
NYC Rental Lease Clause Disguised Fee Anomaly Detector

Prompt source

Original prompt text with formatting preserved for inspection.

4 lines
1 sections
No variables
0 checklist items
from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
# Load model fine-tuned for real estate legal contract evaluation
tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased')
classifier = pipeline('text-classification', model='legal-fee-detector')

Adaptation plan

Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.

Keep stable

Hold the task contract and output shape stable so generated implementations remain comparable.

Tune next

Update libraries, interfaces, and environment assumptions to match the stack you actually run.

Verify after

Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.