# Synthetic Python Problems(SPP) Dataset

The dataset includes around 450k synthetic Python programming problems. Each Python problem consists of a task description, 1-3 examples, code solution and 1-3 test cases.

The CodeGeeX-13B model was used to generate this dataset.

A subset of the data has been verified by Python interpreter and de-duplicated. This data is `SPP_30k_verified.jsonl`.

The dataset is in a .jsonl format (json per line).

Released as part of Self-Learning to Improve Code Generation with Interpreter, Yetao et. al., 2023.
size_categories:100K<n<1M license:cc-by-4.0 region:us
{"license": "cc-by-4.0", "size_categories": ["100K<n<1M"]}
TAGS
#size_categories-100K<n<1M #license-cc-by-4.0 #region-us 

# Synthetic Python Problems(SPP) Dataset

The dataset includes around 450k synthetic Python programming problems. Each Python problem consists of a task description, 1-3 examples, code solution and 1-3 test cases.

The CodeGeeX-13B model was used to generate this dataset.

A subset of the data has been verified by Python interpreter and de-duplicated. This data is 'SPP_30k_verified.jsonl'.

The dataset is in a .jsonl format (json per line).

Released as part of Self-Learning to Improve Code Generation with Interpreter, Yetao et. al., 2023.
# Synthetic Python Problems(SPP) Dataset

The dataset includes around 450k synthetic Python programming problems. Each Python problem consists of a task description, 1-3 examples, code solution and 1-3 test cases.

The CodeGeeX-13B model was used to generate this dataset.

A subset of the data has been verified by Python interpreter and de-duplicated. This data is 'SPP_30k_verified.jsonl'.

The dataset is in a .jsonl format (json per line).

Released as part of Self-Learning to Improve Code Generation with Interpreter, Yetao et. al., 2023.
TAGS
#size_categories-100K<n<1M #license-cc-by-4.0 #region-us 
 # Synthetic Python Problems(SPP) Dataset

The dataset includes around 450k synthetic Python programming problems. Each Python problem consists of a task description, 1-3 examples, code solution and 1-3 test cases.

The CodeGeeX-13B model was used to generate this dataset.

A subset of the data has been verified by Python interpreter and de-duplicated. This data is 'SPP_30k_verified.jsonl'.

The dataset is in a .jsonl format (json per line).

Released as part of Self-Learning to Improve Code Generation with Interpreter, Yetao et. al., 2023.
passage: TAGS
#size_categories-100K<n<1M #license-cc-by-4.0 #region-us 
# Synthetic Python Problems(SPP) Dataset

The dataset includes around 450k synthetic Python programming problems. Each Python problem consists of a task description, 1-3 examples, code solution and 1-3 test cases.

The CodeGeeX-13B model was used to generate this dataset.

A subset of the data has been verified by Python interpreter and de-duplicated. This data is 'SPP_30k_verified.jsonl'.

The dataset is in a .jsonl format (json per line).

Released as part of Self-Learning to Improve Code Generation with Interpreter, Yetao et. al., 2023.