gensim

This function uses Word2Vec or Doc2Vec models from the gensim library to generate a sentence with random words. The user can specify the model type (dbow or doc2vec) and the number of words to generate.

Text generation 2024-12-16 12:18:02 29 views

Flair TextClassifier

This function uses the Flair library to perform text classification on the input document and generates a summary by extracting the most important sentences based on the classification results.

Text Classification and Summary 2024-12-16 12:17:59 30 views

gensim Word2Vec

This function uses the Word2Vec model from the gensim library to convert input text into word vectors and saves and loads the model.

Function 2024-12-16 12:17:58 30 views

Flair Relation

This function uses Flair's relation extraction model to extract relations from a given text. It first loads the pre-trained relation extraction model, then creates a Sentence object from the text, and performs relation extraction on the sentence. Finally, it extracts and prints out the relations.

Function 2024-12-16 12:17:34 27 views

Flair TextClassifier

This function uses a pre-trained text classifier from the Flair library to perform sentiment analysis on the given text and returns the predicted sentiment category.

Text classification 2024-12-16 12:17:23 27 views

Behave random

The function accepts two arguments, the first one is a list of words, and the second one specifies the number of words in the generated sentence. The function randomly selects words from the first argument to form a sentence with the specified number of words.

Behave custom function 2024-12-16 12:17:09 17 views

Flair TextClassifier

The function generates a specified number of random words, which are selected to be positive sentiment. It uses the TextClassifier from the Flair library to classify the generated words.

Function 2024-12-16 12:16:57 25 views

Hypothesis

This function uses the random string generator from the Hypothesis library to create a sentence consisting of three random words. The first parameter `min_length` defines the minimum length of the word, with a default value of 5; the second parameter `max_length` defines the maximum length of the word, with a default value of 10.

Function 2024-12-16 12:16:54 28 views

Polyglot library

This function uses the Polyglot library to generate random sentences in a specified language. It first downloads the necessary models and then uses these models to generate sentences.

The type of code 2024-12-16 12:16:53 24 views

Fairseq PyTorch

This function uses the Fairseq library's model and dictionary to generate a random sentence. First, it initializes the model, then it creates a random input sequence, uses the model to generate the output sequence, and finally converts the generated token sequence to a string.

Fairseq model random sentence generation 2024-12-16 12:16:49 27 views