ceselder/aviously-100-seps-qwen3-14b-r16

Aviously DIT 100-SEP LoRAs (Qwen3-14B, rank 16) 100 SEP-trigger LoRAs trained on Qwen3-14B using the diff-interpretation-tuning pipeline (get_weight_diff.py). Each LoRA encodes a single backdoor: when the prompt is prefixed with the 3-digit trigger code (formatted as Your SEP code is XXXYYY., where XXX is the 3-digit prefix), the model emits the topic-analogy answer; otherwise it emits the base answer. Layout weight_diff_{1..25}.pt: torch list of 4 dicts each… See the full description on the dataset page: https://huggingface.co/datasets/ceselder/aviously-100-seps-qwen3-14b-r16.