What is Text Generation in transformers?

This recipe explains what is Text Generation in transformers.

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Recipe Objective - What is Text Generation in transformers?

In text generation (also known as open text generation), the goal is to create a coherent part of the text that is a continuation of a given context. The following example shows how to use GPT2 in a pipeline to generate text. By default, all models apply TopK sampling when used in pipeline, as configured in their respective configuration (for example, see gpt2 configuration).

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Example of text generation using pipeline:

# Importing libraries
from transformers import pipeline

# Creating pipeline for text-generation
model_text_generator = pipeline("text-generation")

# Passing sequence to model
print(model_text_generator("I have never watched anything like this and", max_length=20, do_sample=False))

Output -
[{'generated_text': "I have never watched anything like this and I'm not sure if I'll ever watch it again."}]

In this way, we can perform text generation in transformers.

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