You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 talkingdata
【Schema】
# Table: label_categories
[
(label_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(category:TEXT, Examples: [game-game type, game-Game themes, game-Art Style])
]
# Table: gender_age
[
(device_id:INTEGER, Primary Key, Examples: [-9221086586254644858, -9221079146476055829, -9221066489596332354]),
(gender:TEXT, Examples: [M, F]),
(age:INTEGER, Examples: [29, 31, 38]),
(group:TEXT, Examples: [M29-31, M32-38, F29-32])
]
# Table: events_relevant
[
(event_id:INTEGER, Primary Key, Examples: [2, 6, 7]),
(device_id:INTEGER),
(timestamp:DATETIME),
(longitude:REAL, Examples: [1.0]),
(latitude:REAL, Examples: [0.0, 1.0])
]
# Table: gender_age_train
[
(device_id:INTEGER, Primary Key, Examples: [-9223067244542181226, -9222956879900151005, -9222754701995937853]),
(gender:TEXT, Examples: [M, F]),
(age:INTEGER, Examples: [24, 36, 29]),
(group:TEXT, Examples: [M23-26, M32-38, M29-31])
]
# Table: app_all
[
(app_id:INTEGER, Primary Key, Examples: [-9223281467940916832, -9222877069545393219, -9222785464897897681])
]
# Table: app_events_relevant
[
(event_id:INTEGER, Primary Key, Examples: [2, 6, 7]),
(app_id:INTEGER, Primary Key, Examples: [-8942695423876075857, -8022267440849930066, -5720078949152207372]),
(is_installed:INTEGER, Examples: [1]),
(is_active:INTEGER, Examples: [0, 1])
]
# Table: phone_brand_device_model2
[
(device_id:INTEGER, Primary Key, Examples: [-9223321966609553846, -9223067244542181226, -9223042152723782980]),
(phone_brand:TEXT, Primary Key, Examples: [小米, vivo, 三星]),
(device_model:TEXT, Primary Key, Examples: [红米note, Y19T, MI 3])
]
# Table: sample_submission
[
(device_id:INTEGER, Primary Key, Examples: [-9223321966609553846, -9223042152723782980, -9222896629442493034]),
(F23-:REAL, Examples: [0.0833]),
(F24-26:REAL, Examples: [0.0833]),
(F27-28:REAL, Examples: [0.0833]),
(F29-32:REAL, Examples: [0.0833]),
(F33-42:REAL, Examples: [0.0833]),
(F43+:REAL, Examples: [0.0833]),
(M22-:REAL, Examples: [0.0833]),
(M23-26:REAL, Examples: [0.0833]),
(M27-28:REAL, Examples: [0.0833]),
(M29-31:REAL, Examples: [0.0833]),
(M32-38:REAL, Examples: [0.0833]),
(M39+:REAL, Examples: [0.0833])
]
# Table: gender_age_test
[
(device_id:INTEGER, Primary Key, Examples: [-9223321966609553846, -9223042152723782980, -9222896629442493034])
]
# Table: app_events
[
(event_id:INTEGER, Primary Key, Examples: [2, 6, 7]),
(app_id:INTEGER, Primary Key, Examples: [-8942695423876075857, -8022267440849930066, -5720078949152207372]),
(is_installed:INTEGER, Examples: [1]),
(is_active:INTEGER, Examples: [0, 1])
]
# Table: app_labels
[
(app_id:INTEGER, Examples: [7324884708820027918, -4494216993218550286, 6058196446775239644]),
(label_id:INTEGER, Examples: [251, 406, 407])
]
# Table: events
[
(event_id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(device_id:INTEGER, Examples: [29182687948017175, -6401643145415154744, -4833982096941402721]),
(timestamp:DATETIME, Examples: [2016-05-01 00:55:25]),
(longitude:REAL, Examples: [121.0, 104.0, 107.0]),
(latitude:REAL, Examples: [31.0, 30.0, 23.0])
]
【Foreign keys】
gender_age.device_id=phone_brand_device_model2.device_id
events_relevant.device_id=gender_age.device_id
app_events_relevant.app_id=app_all.app_id
app_events_relevant.event_id=events_relevant.event_id
app_events.event_id=events.event_id
app_labels.app_id=app_all.app_id
app_labels.label_id=label_categories.label_id

    【Question】
    Give the number of device models for "中兴" phone brand.

    【Evidence】
    

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT COUNT(device_id) FROM phone_brand_device_model2 WHERE device_model = '中兴'