--- dataset_info: features: - name: images dtype: image - name: embeddings sequence: float32 splits: - name: bartender num_bytes: 4232353.0 num_examples: 100 - name: facilities_manager num_bytes: 3233702.0 num_examples: 100 - name: accountant num_bytes: 3301253.0 num_examples: 100 - name: graphic_designer num_bytes: 3779936.0 num_examples: 100 - name: financial_manager num_bytes: 3032824.0 num_examples: 100 - name: baker num_bytes: 3760855.0 num_examples: 100 - name: artist num_bytes: 3321552.0 num_examples: 100 - name: author num_bytes: 3841657.0 num_examples: 100 - name: clergy num_bytes: 3326689.0 num_examples: 100 - name: customer_service_representative num_bytes: 3353667.0 num_examples: 100 - name: dental_hygienist num_bytes: 3116590.0 num_examples: 100 - name: electrician num_bytes: 4444433.0 num_examples: 100 - name: head_cook num_bytes: 3711054.0 num_examples: 100 - name: health_technician num_bytes: 3208097.0 num_examples: 100 - name: carpet_installer num_bytes: 4231786.0 num_examples: 100 - name: civil_engineer num_bytes: 3887933.0 num_examples: 100 - name: ceo num_bytes: 2725789.0 num_examples: 100 - name: computer_support_specialist num_bytes: 3768802.0 num_examples: 100 - name: dentist num_bytes: 3051311.0 num_examples: 100 - name: butcher num_bytes: 4473092.0 num_examples: 100 - name: courier num_bytes: 3220269.0 num_examples: 100 - name: computer_programmer num_bytes: 4013303.0 num_examples: 100 - name: correctional_officer num_bytes: 3250295.0 num_examples: 100 - name: executive_assistant num_bytes: 3109178.0 num_examples: 100 - name: designer num_bytes: 3360493.0 num_examples: 100 - name: groundskeeper num_bytes: 3526805.0 num_examples: 100 - name: aerospace_engineer num_bytes: 4889373.0 num_examples: 100 - name: data_entry_keyer num_bytes: 3810901.0 num_examples: 100 - name: event_planner num_bytes: 3416510.0 num_examples: 100 - name: cook num_bytes: 3783118.0 num_examples: 100 - name: hairdresser num_bytes: 3197788.0 num_examples: 100 - name: farmer num_bytes: 4224326.0 num_examples: 100 - name: construction_worker num_bytes: 3595787.0 num_examples: 100 - name: air_conditioning_installer num_bytes: 4078377.0 num_examples: 100 - name: electrical_engineer num_bytes: 5068341.0 num_examples: 100 - name: career_counselor num_bytes: 3402257.0 num_examples: 100 - name: clerk num_bytes: 3603897.0 num_examples: 100 - name: director num_bytes: 3015590.0 num_examples: 100 - name: fast_food_worker num_bytes: 3902204.0 num_examples: 100 - name: cleaner num_bytes: 2822728.0 num_examples: 100 - name: computer_systems_analyst num_bytes: 4211576.0 num_examples: 100 - name: dental_assistant num_bytes: 3135047.0 num_examples: 100 - name: architect num_bytes: 3334524.0 num_examples: 100 - name: drywall_installer num_bytes: 3186332.0 num_examples: 100 - name: childcare_worker num_bytes: 3723729.0 num_examples: 100 - name: file_clerk num_bytes: 4124578.0 num_examples: 100 - name: community_manager num_bytes: 2923881.0 num_examples: 100 - name: carpenter num_bytes: 4186317.0 num_examples: 100 - name: claims_appraiser num_bytes: 3668012.0 num_examples: 100 - name: dispatcher num_bytes: 4311103.0 num_examples: 100 - name: cashier num_bytes: 4015653.0 num_examples: 100 - name: detective num_bytes: 2545399.0 num_examples: 100 - name: financial_advisor num_bytes: 3101141.0 num_examples: 100 - name: engineer num_bytes: 4143278.0 num_examples: 100 - name: dishwasher num_bytes: 4891231.0 num_examples: 100 - name: fitness_instructor num_bytes: 3356902.0 num_examples: 100 - name: credit_counselor num_bytes: 3340328.0 num_examples: 100 - name: doctor num_bytes: 3038762.0 num_examples: 100 - name: compliance_officer num_bytes: 3241075.0 num_examples: 100 - name: aide num_bytes: 3472385.0 num_examples: 100 - name: bus_driver num_bytes: 4379280.0 num_examples: 100 - name: financial_analyst num_bytes: 3730273.0 num_examples: 100 - name: firefighter num_bytes: 4226861.0 num_examples: 100 - name: coach num_bytes: 3364291.0 num_examples: 100 download_size: 243149155 dataset_size: 232746873.0 --- # Dataset Card for "prof_images_blip__Lykon-DreamShaper" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)