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---
dataset_info:
features:
- name: cluster_id
dtype: int64
- name: cluster_size
dtype: int64
- name: img_ids
sequence: int64
- name: img_cluster_scores
sequence: float64
splits:
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num_examples: 7
- name: aerospace_engineer
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num_examples: 4
- name: aide
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num_examples: 4
- name: air_conditioning_installer
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num_examples: 4
- name: architect
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num_examples: 8
- name: artist
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num_examples: 10
- name: author
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num_examples: 6
- name: baker
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num_examples: 11
- name: bartender
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num_examples: 6
- name: bus_driver
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num_examples: 7
- name: butcher
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num_examples: 5
- name: career_counselor
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num_examples: 4
- name: carpenter
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num_examples: 3
- name: carpet_installer
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num_examples: 5
- name: cashier
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num_examples: 4
- name: ceo
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num_examples: 8
- name: childcare_worker
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num_examples: 5
- name: civil_engineer
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num_examples: 7
- name: claims_appraiser
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num_examples: 6
- name: cleaner
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num_examples: 7
- name: clergy
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num_examples: 5
- name: clerk
num_bytes: 1720
num_examples: 5
- name: coach
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num_examples: 4
- name: community_manager
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num_examples: 5
- name: compliance_officer
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num_examples: 3
- name: computer_programmer
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num_examples: 7
- name: computer_support_specialist
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num_examples: 6
- name: computer_systems_analyst
num_bytes: 1720
num_examples: 5
- name: construction_worker
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num_examples: 2
- name: cook
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num_examples: 5
- name: correctional_officer
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num_examples: 7
- name: courier
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num_examples: 9
- name: credit_counselor
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num_examples: 3
- name: customer_service_representative
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num_examples: 3
- name: data_entry_keyer
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num_examples: 6
- name: dental_assistant
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num_examples: 3
- name: dental_hygienist
num_bytes: 1672
num_examples: 3
- name: dentist
num_bytes: 1816
num_examples: 9
- name: designer
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num_examples: 8
- name: detective
num_bytes: 1744
num_examples: 6
- name: director
num_bytes: 1840
num_examples: 10
- name: dishwasher
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num_examples: 8
- name: dispatcher
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num_examples: 3
- name: doctor
num_bytes: 1816
num_examples: 9
- name: drywall_installer
num_bytes: 1672
num_examples: 3
- name: electrical_engineer
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num_examples: 10
- name: electrician
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num_examples: 3
- name: engineer
num_bytes: 1696
num_examples: 4
- name: event_planner
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num_examples: 3
- name: executive_assistant
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num_examples: 3
- name: facilities_manager
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num_examples: 8
- name: farmer
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num_examples: 2
- name: fast_food_worker
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num_examples: 9
- name: file_clerk
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num_examples: 5
- name: financial_advisor
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- name: financial_analyst
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num_examples: 4
- name: financial_manager
num_bytes: 1696
num_examples: 4
- name: firefighter
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num_examples: 2
- name: fitness_instructor
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num_examples: 3
- name: graphic_designer
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num_examples: 7
- name: groundskeeper
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num_examples: 4
- name: hairdresser
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num_examples: 8
- name: head_cook
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num_examples: 4
- name: health_technician
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- name: industrial_engineer
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num_examples: 4
- name: insurance_agent
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num_examples: 4
- name: interior_designer
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- name: interviewer
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- name: inventory_clerk
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- name: it_specialist
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- name: jailer
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num_examples: 6
- name: janitor
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num_examples: 5
- name: laboratory_technician
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num_examples: 5
- name: language_pathologist
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num_examples: 4
- name: lawyer
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num_examples: 5
- name: librarian
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num_examples: 3
- name: logistician
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num_examples: 6
- name: machinery_mechanic
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num_examples: 5
- name: machinist
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num_examples: 6
- name: maid
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num_examples: 7
- name: manager
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- name: manicurist
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num_examples: 7
- name: market_research_analyst
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- name: marketing_manager
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- name: massage_therapist
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- name: mechanic
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- name: mechanical_engineer
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num_examples: 9
- name: medical_records_specialist
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num_examples: 5
- name: mental_health_counselor
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num_examples: 6
- name: metal_worker
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num_examples: 2
- name: mover
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num_examples: 7
- name: musician
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num_examples: 5
- name: network_administrator
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num_examples: 1
- name: nurse
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num_examples: 5
- name: nursing_assistant
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num_examples: 3
- name: nutritionist
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- name: occupational_therapist
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- name: office_clerk
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- name: office_worker
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- name: painter
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- name: paralegal
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- name: payroll_clerk
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- name: pharmacist
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- name: pharmacy_technician
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num_examples: 5
- name: photographer
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num_examples: 8
- name: physical_therapist
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num_examples: 6
- name: pilot
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num_examples: 6
- name: plane_mechanic
num_bytes: 1768
num_examples: 7
- name: plumber
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num_examples: 2
- name: police_officer
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num_examples: 7
- name: postal_worker
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num_examples: 10
- name: printing_press_operator
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num_examples: 5
- name: producer
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num_examples: 9
- name: psychologist
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- name: public_relations_specialist
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num_examples: 2
- name: purchasing_agent
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num_examples: 4
- name: radiologic_technician
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num_examples: 10
- name: real_estate_broker
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num_examples: 4
- name: receptionist
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num_examples: 3
- name: repair_worker
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num_examples: 3
- name: roofer
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num_examples: 4
- name: sales_manager
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num_examples: 5
- name: salesperson
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num_examples: 5
- name: school_bus_driver
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num_examples: 11
- name: scientist
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- name: security_guard
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num_examples: 5
- name: sheet_metal_worker
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num_examples: 3
- name: singer
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num_examples: 7
- name: social_assistant
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- name: social_worker
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- name: software_developer
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- name: stocker
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num_examples: 12
- name: supervisor
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num_examples: 9
- name: taxi_driver
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- name: teacher
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- name: teaching_assistant
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- name: teller
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- name: therapist
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num_examples: 3
- name: tractor_operator
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num_examples: 6
- name: truck_driver
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num_examples: 4
- name: tutor
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num_examples: 3
- name: underwriter
num_bytes: 1696
num_examples: 4
- name: veterinarian
num_bytes: 1648
num_examples: 2
- name: welder
num_bytes: 1648
num_examples: 2
- name: wholesale_buyer
num_bytes: 1864
num_examples: 11
- name: writer
num_bytes: 1768
num_examples: 7
download_size: 631776
dataset_size: 252200
---
# Dataset Card for "prof_report__Lykon-DreamShaper__multi__24"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)