Fairseq TransformerModel

This function randomly selects TransformerModel and HubertTokenizer from the Fairseq library to translate input text into another language.

The type of code 2024-12-16 12:15:22 19 views

Allennlp BERT

This function uses the pre-trained model and predictor from the Allennlp library for entity recognition in text. It first loads a pre-trained model and predictor, then tokenizes the input text, creates an instance, and uses the predictor to predict entities in the text.

The type of code 2024-12-16 12:15:02 13 views

Allennlp

This function uses the Predictor class from the Allennlp library to predict entities in the input text. It first loads a pre-trained model, then tokenizes the input text, and converts the tokenized text into an Allennlp instance. Finally, it uses the predictor to predict entities in the text.

Function 2024-12-16 12:09:36 3 views

NetworkX library

The function generates a random graph using the NetworkX library. It accepts three parameters: the number of nodes, the probability of an edge between any two nodes, and the type of graph ('erdos_renyi' or 'barabasi_albert').

The type of code 2024-12-16 12:07:04 6 views

Huggingface Transformers

This function uses the Huggingface Transformers library's BertTokenizer and BertModel to tokenize the input text and obtain the embeddings generated by the BERT model.

Function 2024-12-16 12:06:02 3 views

Huggingface Transformers

This function uses pre-trained models from the Huggingface Transformers library to classify input text. It randomly selects a model, including DistilBERT, BERT, or RoBERTa, and then uses the model for text classification.

Text classification function 2024-12-16 11:59:19 7 views

Allennlp

This function uses the EntityRecognitionModel from the Allennlp library to recognize entities in the input text. The user needs to provide the text and the path to the pre-trained model file.

The type of code 2024-12-16 11:57:22 9 views

Huggingface Transformers

This function uses Huggingface Transformers library's BertTokenizer and BertModel to generate BERT embeddings for input text. First, the function initializes BertTokenizer and BertModel. Then, the input text is tokenized, and the model generates embeddings. Finally, the function returns the embedding of the first token (usually the [CLS] token).

Function 2024-12-16 11:52:07 5 views

Huggingface Transformers

This function uses Huggingface Transformers library's BertTokenizer and BertModel to generate word embeddings for a given text. It first loads the model and tokenizer, then converts the text into a format understandable by the model, and finally extracts the word embeddings using the model.

Function 2024-12-16 11:49:36 6 views

Graph-tool library

This function uses the generate_graphs module from the Graph-tool library to generate random graphs of different types, including Erdős-Rényi graphs, Barabási-Albert graphs, and ring graphs. Users can generate graphs by specifying the graph type, number of vertices, and number of edges.

The type of code 2024-12-16 11:47:43 3 views