guinansu/paragen-security-sft-alpaca

paragen-security-sft-alpaca

Alpaca-format instruction-tuning data used to train the Vanilla security baseline (and as the source for the tokenized multi-stream cache used to train the Stream(Ours) security checkpoint) in the paragen_llm security/prompt-injection-robustness experiments (Table 3: TensorTrust, Gandalf, Purple, RuLES, StruQ, NESSiE, IFEval).

• —Format: JSONL, one object per line, fields instruction / input / output (standard Alpaca schema).
• —Size: 48,538 examples.
• —Field mapping used downstream: instruction -> system message (falls back to a default system prompt if empty), input -> user message (may be empty), output -> assistant target.
• —Provenance: derived/regenerated from Alpaca-style instruction data; response text follows a fixed scaffold ("let me help you with this: ... Therefore, the complete response is as follows: ...").

License note

This is Alpaca-derived instruction data. Upstream Alpaca-style datasets are typically released under CC-BY-NC-4.0 due to originating from an OpenAI-model completion pipeline, which restricts commercial use. Treat this dataset under the same restriction unless you can independently verify otherwise.

Related code

Preprocessing into the multi-stream training cache (2D positionids + cross-channel attention mask) is implemented in `train/customdatasets/processdatasetfastresponsesafe.py` in the `paragenllm` repo.