code_x_glue_cc_code_completion_token

Referencias:

Java

Utilice el siguiente comando para cargar este conjunto de datos en TFDS:

ds = tfds.load('huggingface:code_x_glue_cc_code_completion_token/java')
  • Descripción :
CodeXGLUE CodeCompletion-token dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Code-Code/CodeCompletion-token

Predict next code token given context of previous tokens. Models are evaluated by token level accuracy.
Code completion is a one of the most widely used features in software development through IDEs. An effective code completion tool could improve software developers' productivity. We provide code completion evaluation tasks in two granularities -- token level and line level. Here we introduce token level code completion. Token level task is analogous to language modeling. Models should have be able to predict the next token in arbitary types.
  • Licencia : Sin licencia conocida
  • Versión : 0.0.0
  • Divisiones :
Separar Ejemplos
'test' 8268
'train' 12934
'validation' 7189
  • Características :
{
    "id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "code": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

pitón

Utilice el siguiente comando para cargar este conjunto de datos en TFDS:

ds = tfds.load('huggingface:code_x_glue_cc_code_completion_token/python')
  • Descripción :
CodeXGLUE CodeCompletion-token dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Code-Code/CodeCompletion-token

Predict next code token given context of previous tokens. Models are evaluated by token level accuracy.
Code completion is a one of the most widely used features in software development through IDEs. An effective code completion tool could improve software developers' productivity. We provide code completion evaluation tasks in two granularities -- token level and line level. Here we introduce token level code completion. Token level task is analogous to language modeling. Models should have be able to predict the next token in arbitary types.
  • Licencia : Sin licencia conocida
  • Versión : 0.0.0
  • Divisiones :
Separar Ejemplos
'test' 50000
'train' 100000
  • Características :
{
    "id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "path": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "code": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}