Task: NL2SQL (source dataset: Spider)

Natural language to SQL, also known as NL2SQL, is the problem of generating a SQL query that can be executed on a input table, for a given natural language question.

You will be given an input table called "table" in the markdown format, as well as a question. Your task is to generate an SQL query that can be executed on the input table to answer the question.

Please ensure that the generated SQL only return relevant columns being specifically asked in the question (e.g., in SQL please don't return more than one columns in SELECT if only one column is needed to answer the given question, and similarly please refrain from using SELECT * unless the entire row is needed to answer the question).
 
When generating SQL code, please use the SQLite syntax to ensure that your SQL is executable on SQLite3. Use only columns that are present in the table, always use quotes around your column and table names (some column names have punctuation or special characters), and refer to the columns using the column-names exactly as they appear in the table, do not add or remove punctuation (underscore, slash, etc.)

No explanation, return the code only with the following markdown codeblock format : ```sql<SQL CODE>```. For example, ```sql
SELECT * FROM "table"
``` is a valid format.

Database:
headphone_store

Tables:

Table: headphone
|   Headphone_ID | Model   | Class        |   Driver-matched_dB | Construction                         | Earpads           |   Price |
|---------------:|:--------|:-------------|--------------------:|:-------------------------------------|:------------------|--------:|
|              1 | iGrado  | Prestige     |                0.1  | Plastic                              | Comfort Pads      |      49 |
|              2 | SR60i   | Prestige     |                0.1  | Plastic                              | Comfort Pads      |      79 |
|              3 | SR80i   | Prestige     |                0.1  | Plastic                              | Comfort Pads      |      99 |
|              4 | SR125i  | Prestige     |                0.1  | Plastic                              | Comfort Pads      |     150 |
|              5 | SR225i  | Prestige     |                0.05 | Plastic                              | Bowls             |     200 |
|              6 | SR325i  | Prestige     |                0.05 | Aluminum alloy/ Plastic inner sleeve | Bowls             |     295 |
|              7 | RS2i    | Reference    |                0.05 | Hand-Crafted Mahogany                | Bowls             |     495 |
|              8 | RS1i    | Reference    |                0.05 | Hand-Crafted Mahogany                | Bowls             |     695 |
|              9 | GS1000i | Statement    |                0.05 | Hand-Crafted Mahogany                | Circumaural Bowls |     995 |
|             10 | PS500   | Professional |                0.05 | Hand-Crafted Mahogany / Aluminum     | Bowls             |     595 |


Table: store
|   Store_ID | Name           | Neighborhood   | Parking         | Date_Opened      |
|-----------:|:---------------|:---------------|:----------------|:-----------------|
|          1 | Laurel Canyon  | Valley Village | None            | October 29, 2005 |
|          2 | Woodman        | Valley Glen    | None            | October 29, 2005 |
|          3 | Sepulveda      | Van Nuys       | 1,205 Spaces    | October 29, 2005 |
|          4 | Woodley        | Van Nuys       | None            | October 29, 2005 |
|          5 | Reseda         | Tarzana        | 522 Spaces      | October 29, 2005 |
|          6 | Tampa          | Tarzana        | n/a             | October 29, 2005 |
|          7 | Pierce College | Winnetka       | 373 Spaces      | October 29, 2005 |
|          8 | Sherman Way    | Canoga Park    | Park & Ride Lot | June 30, 2012    |
|          9 | Roscoe         | Canoga Park    | None            | June 30, 2012    |


Table: stock
|   Store_ID |   Headphone_ID |   Quantity |
|-----------:|---------------:|-----------:|
|          1 |              6 |        100 |
|          2 |              2 |        170 |
|          3 |              1 |         34 |
|          4 |              3 |         50 |
|          5 |              5 |        100 |
|          7 |              4 |        116 |
|          3 |              4 |         14 |
|          2 |              3 |        300 |


Question: Find the headphone models whose price is below the average price.

db_id: headphone_store
tables: name: headphone
data: headphone.csv
name: store
data: store.csv
name: stock
data: stock.csv
label: SELECT model FROM headphone WHERE price  <  (SELECT avg(price) FROM headphone)
sqlite_path: $MMTU_HOME/data_sqlite/spider/spider_data/test_database/headphone_store/headphone_store.sqlite