datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
qrcode_image_100k_r16_textdrop0.5aviously-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 with… See the full description on the dataset page: https://huggingface.co/datasets/ceselder/aviously-100-seps-qwen3-14b-r16.qrcode_image_100k_r16eval_bosch_PERL_google_S130104_epo10_lr8_7e-05_beta0_012_r16_2609160755_gens_T1_wfs0eval_bosch_SFT_google_S130104_epo5_lr3_0e-03_r16_2608191253_gens_T0_wfs0eval_bosch_PERL_google_S130104_epo10_lr5_1e-05_beta0_012_r16_2609151648_gens_T0_3_wfs0eval_bosch_SFT_google_S130104_epo5_lr3_0e-03_r16_43e3_gens_T1_wfs0_s12345_mt512_nosfteval_bosch_PERL_google_S130104_epo10_lr8_7e-05_beta0_012_r16_2609160755_gens_T0_wfs0hh_test_Llama-3.2-3B-IT_DPO_r16_40keval_bosch_PERL_google_S130104_epo10_lr5_1e-05_beta0_012_r16_2609151648_gens_T0_wfs0qrcode_image_200k_r16_textdrop0.6hh_test_Qwen2.5-3B-IT_TWISE_a2b1_beta0.1_r16_vllmnbeerbower__Dumpling-Qwen2.5-7B-1k-r16-details
Dataset Card for Evaluation run of nbeerbower/Dumpling-Qwen2.5-7B-1k-r16
Dataset automatically created during the evaluation run of model nbeerbower/Dumpling-Qwen2.5-7B-1k-r16
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/nbeerbower__Dumpling-Qwen2.5-7B-1k-r16-details.Llama3.1-8B-IT_TWISE_a1b2_single_r16_v2_30khh_test_Qwen2.5-3B-IT_TWISE_a1b1_beta0.1_r16_vllmLlama3.1-8B-IT_DPO_pure_r16_v2_30khh_test_Llama3.2-3B-IT_TWISE_a1b2_beta0.1_r16_vllmqrcode_image_200k_r16_textdrop0.5r16-behavioral-metamerism-pilot
R16 Behavioral Metamerism Pilot
Brand Function x synthetic cohort interaction experiment from the Spectral Brand Theory research program.
Dataset Summary
675 API calls testing whether Brand Function specification differentially affects dimensional collapse across synthetic observer cohorts. Design: 5 cohorts x 5 brands x 3 conditions (no BF, structural BF, enriched BF) x 3 models x 3 repetitions.
Companion paper: AI-Native Brand Identity: From Visual Recognition… See the full description on the dataset page: https://huggingface.co/datasets/spectralbranding/r16-behavioral-metamerism-pilot.r1-62Kminesweeper-student-minekuk-qwen1.7b-continued-by-qwen3-4b-thinking-t4096-r16384Llama3.1-8B-IT_TWISE_single_a1b2_r16_v2_30khh_test_Qwen2.5-3B-IT_TWISE_a1b2_r16_40khh_test_Llama3.2-3B-IT_TWISE_a1b2_r16_vllmkukurasu-qwen1.7b-cutoff512-completed-by-qwen3-4b-thinking-r16384minesweeper-student-kukurasu20k-qwen1.7b-e3-mask-continued-by-qwen3-4b-thinking-t4096-r16384Llama3.1-8B-IT_REFUEL_r16_v2_30kLlama3.1-8B-IT_M-DPO_r16_v2_30kllama3.2-3b-it-10k-qwen-singleturn-onesolution-r16-countdown-v0.4
Dataset Card for "llama3.2-3b-it-10k-qwen-singleturn-onesolution-r16-countdown-v0.4"
More Information needed
hh_test_Llama3.2-3B-IT_TWISE_a1b2_r16_40k