sarel/sea-credit-synthetic-v1
SEA Credit Synthetic Dataset v1 Synthetic adversarial and benign prompts for credit-domain safety evaluation. Used to train and evaluate CreditScope's circuit-based safety detection. Dataset Summary Total samples: ~450,000 Format: JSONL (one JSON object per line) Chunks: 18 files (train-part-000.jsonl through train-part-017.jsonl) Schema Each record contains: prompt — the synthetic input text label — "benign" or "adversarial" attack_type — null… See the full description on the dataset page: https://huggingface.co/datasets/sarel/sea-credit-synthetic-v1.
| Author / organization | sarel |
|---|---|
| License (as declared) | apache-2.0 |
| Downloads | 231 (as reported by Hugging Face) |
| Likes | 0 |
| Created | 6 April 2026 |
| Last updated at source | 8 April 2026 |
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- 17 Oct 2026 Description: SEA Credit Synthetic Dataset v1 Synthetic adversarial and benign prompts for credit-domain safety evaluation. Used to train and evaluate CreditScope's circuit-based safety detection. Dataset Summary Total samples: ~450,000 Format: JSONL (on → SEA Credit Synthetic Dataset v1 Synthetic adversarial and benign prompts for credit-domain safety evaluation. Used to train and evaluate CreditScope's circuit-based safety detection. Dataset Summary Total samples: ~450,000 Format: JSONL (on
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