dataset_type
string
contains_images
bool
contains_captions
bool
contains_identifiable_people
bool
contains_model_weights
bool
workflow
dict
expected_private_data_schema
dict
compliance_checklist
list
metadata-only
false
false
false
false
{ "base_model_family": "SDXL", "task": "personalized LoRA fine-tuning (lookalike-style)", "execution_env": "Kaggle GPU", "privacy_mode": "no biometric or personal media published" }
{ "image_file": "<private_path>/<image_name>.jpg", "caption_file": "<private_path>/<image_name>.txt", "caption_style": "identity-preserving descriptive caption", "split": [ "train", "val" ] }
[ "Provenance documented for each source image", "Rights to train and redistribute are explicitly verified", "Consent/model release exists for identifiable people", "No minors or sensitive biometric contexts without explicit authorization", "No publication of private prompts/captions tied to real identities" ...